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Species of Science Studies
by
Paul Alexander Armstrong
A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy
Department of Sociology University of Toronto
© Copyright by Paul Alexander Armstrong 2013
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Species of Science Studies
Paul Alexander Armstrong
Doctor of Philosophy
Department of Sociology
University of Toronto
2013
Abstract
Following Merton (1942) science studies has moved from the philosophy of science to a more
sociologically minded analysis of scientific activity. This largely involves a shift away from
questions that bear on the context of justification – a question of rationality and philosophy, to
those that deal with the context of discovery. This thesis investigates changes in science studies
in three papers: sociocultural evolutionary theories of scientific change; general trends in science
studies - especially concerning the sociology of science; and a principle component analysis
(PCA) that details the development and interaction between research programmes in science
studies. This thesis describes the proliferation of research programmes in science studies and
uses evolutionary theory to make sense of the pattern of change.
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Acknowledgments
I am deeply indebted to many people for supporting me during this journey and contributing to
this thesis.
Throughout my graduate experience I have increasingly come to realize that mentorship is the
single greatest factor that influences success. I am extremely grateful to my co-supervisor and
mentor Professor Marion Blute for her faith in me and for sticking with me throughout my
graduate career. There is no question that she saved my graduate career and for this I am grateful
beyond words. Professor Blute has been the archtype of a mentor for me throughout the years.
Her unwavering support and commitment helped me through many difficult times. She showed
tremendous patience as I developed into a more mature, responsible student and her influence
has set me on a path in academia that I am excited for.
I wish to thank Professor Zaheer Baber and Professor Bernd Baldus for their help throughout this
process and for their contributions throughout my graduate experience. Between last minute
meetings for comprehensive exams to working together in courses I am most grateful for their
help and mentorship.
I owe a special thanks to the Department of Sociology at the University of Toronto for giving me
the opportunity to conduct my doctoral research. The faculty and staff I have encountered along
the way have been professional, courteous, helpful, and understanding. I have made many friends
along the way and I thank them all for their friendship, patience, and their support as I struggled
both professionally and personally through this sometimes difficult process.
Finally, it is difficult to express in words the feelings of love and gratitude I have for my parents
and my brothers. Had it not been for their unconditional support I would not have had the
confidence in myself to start on this path let alone persevere through the immense challenges I
faced. I deeply regret not completing this thesis before my mother’s passing in July but she, and
my father and brothers, was on my mind throughout my writing. Her strength and courage and
the strength she brought out in all of us during her battle was my single greatest motivation to
complete my research and it continues to motivate me as I start along a new path in life.
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Table of Contents
Abstract ........................................................................................................................................... ii
Acknowledgments .......................................................................................................................... iii
List of Tables ................................................................................................................................ vii
List of Figures ................................................................................................................................ ix
Chapter 1 Introduction .................................................................................................................... 1
Chapter 2 Unraveling Scientific Development: Sociocultural Evolutionary Theories of
Science as a Process. .................................................................................................................. 4
1 Evolutionary Theory and Cultural Change ................................................................................ 4
2 General Theories of Scientific Change ...................................................................................... 4
3 Scientific Change: Variation, Selection, Reproduction, Pattern. ............................................... 5
4 Primary Considerations .............................................................................................................. 6
5 Evolutionary Theories of Science .............................................................................................. 8
5.1 Thomas Kuhn ...................................................................................................................... 8
5.2 Stephen Toulmin ................................................................................................................. 9
5.3 Karl Popper ....................................................................................................................... 10
5.4 David Hull ......................................................................................................................... 12
5.5 Marion Blute & Paul Armstrong ....................................................................................... 13
6 Debates and Criticism .............................................................................................................. 14
7 Conclusion................................................................................................................................ 15
Chapter 3 Reports of the Death of the Sociology of Science Have Been Greatly Exaggerated ... 16
8 Introduction: The legend .......................................................................................................... 16
9 Data source and methods ......................................................................................................... 20
10 Research questions and results ................................................................................................. 22
10.1 Has the sociology of science become extinct? .................................................................. 22
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10.2 Given that it has not become extinct, has the “sociology of science” continued to be
dominated by its parent, the “sociology of knowledge”, or come to be dominated by
newer offshoots - for example the “sociology of scientific knowledge”, “social studies
of science”, “social epistemology”, or “scientometrics”? ................................................ 23
10.3 Whatever the appropriate description of the level of institutionalization achieved (e.g.
topic, field, research programme, paradigm, discipline etc.), does the sociology of
knowledge, sociology of science and the newer enterprises constitute distinct
‘species’ in the sense that they are socially isolated from each other and fail to
intercommunicate (in the way that members of different biological species fail to
exchange genes or speakers of different languages fail to communicate with each
other)? Or, on the other hand, are they varieties of the same species? ............................. 24
11 Conclusion................................................................................................................................ 26
Chapter 4 The Evolution of Research Programmes: An Author Co-citation Analysis of
Science Studies, 1949-2011 ..................................................................................................... 34
12 Introduction .............................................................................................................................. 34
13 Sociology of Science and Theories of Scientific Change ........................................................ 34
14 Data Source and Methods ........................................................................................................ 37
15 Author Co-citation Analysis .................................................................................................... 38
16 Selection of Authors ................................................................................................................. 39
17 Proximity Matrix, Factor Analysis ........................................................................................... 40
18 Findings: 1964-1978 ................................................................................................................ 40
19 Findings: 1979-1993 ................................................................................................................ 45
20 Findings: 1994-2011 ................................................................................................................ 50
21 Discussion ................................................................................................................................ 55
21.1 What is the level of substantive variation in science studies? .......................................... 55
21.2 How has this variation changed in time? .......................................................................... 55
21.3 What accounts for this change? ........................................................................................ 56
22 Conclusion................................................................................................................................ 58
Chapter 5 Species of Science Studies ........................................................................................... 64
23 Numerical Taxonomy ............................................................................................................... 64
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24 Evolutionary Taxonomy ........................................................................................................... 65
25 Cladistic Analysis..................................................................................................................... 65
References ..................................................................................................................................... 66
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List of Tables
Table 1: Correlation of Publication Counts
Table 1.1: Selection of Authors to Include in Factor Analysis: Mean citation count of authors by
research programme and time period.
Table 2: The Main Ideas for Each Component by Time Period
Table 2.1: Total Variance of Author Co-Citation Counts by Extracted Factors: 1964-1978
Table 2.2: Correlation between Authors and Components: 1964-1978
Table 2.3: The Correlation between Components: 1964-1978
Table 3.1: Total Variance of Author Co-Citation Counts by Extracted Factors: 1979-1993
Table 3.2: Correlation between Authors and Components: 1979-1993
Table 3.3: The Correlation between Components: 1979-1999
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Table 4.1: Research Programmes and Authors Included in Component 1: 1994-2011
Table 4.2: Total Variance of Author Co-Citation Counts by Extracted Factors: 1994-2011
Table 4.3: Correlation between Authors and Components: 1994-2011
Table 4.4: The Correlation between Components: 1994-2011
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List of Figures
Figure 1: Sociology of Science Counts
Figure 2: Science Studies Publications – Proportionally
Figure 3: Proportion of More Constructionist/Non-Constructionist Publications
Figure 4: Proportion of Articles Published in Sociology or More Constructionist Journals
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Chapter 1 Introduction
Science studies have undergone many iterations since the publication of Robert Merton’s path
breaking ‘The Normative Structure of Science’ (1942). He demonstrated that, like any other
institution, the direction science takes is enabled and constrained by socio-structural factors and
institutional norms. Merton’s (1937, 1942) functionalist sociology of science introduces
communalism, universalism, distinterestness, originality, and skepticism into science studies.
These norms are used to explain the institutional characteristics of science and how they interact
with variables like status to explain scientific change. Merton’s analysis effectively shifts the
discourse from the philosophy of science to one that is sociologically minded. With it science
studies move away from questions that bear on the “context of justification” – a question of
rationality and philosophy, to those that deal with the “context of discovery” (Leydesdorff, 1989;
Dolby, 1971; Hess, 1997; Armstrong & Blute, 2010). In this intellectual context studies of
science broadly view science as socio-cultural practice (Callon, 2001). The strong program of the
sociology of scientific knowledge (SSK) is an area of research broadly characterized by
constructionism in its approach to sociological knowledge and reflects the dissolution of the
distinction between discovery and justification (Bloor, 1976; Hess, 1997; Armstrong & Blute,
2010).1 Hess’s “where the field is moving” coincides with Sismondo’s (2008) and Yearley‘s
(2005) account and brings the area to its current point. It broadly features cultural studies of
science, actor-network theory, ethnomethodology, and what Callon (2001) terms “extended
translation.”
In the following three papers I investigate these changes in three ways: sociocultural
evolutionary theories of scientific change; general trends in science studies - especially
1 Kuhn’s (1962) ‘The Structure of Scientific Revolutions’ also dissolves the boundary between discovery and
justification as unique analytical components of science. Kuhn wants to overcome the shortcomings of the two
prominent programmes at the time of his writing: sociological and scientometric approaches. I will elaborate on
scientometrics in the second paper.
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concerning the sociology of science; and a principle component analysis (PCA) that details the
development and interaction between research programs in science studies.
‘Unraveling Scientific Development: Sociocultural Evolutionary Theories of Science as a
Process’ is my argument for using evolutionary theory to pattern developments in science
studies. In this paper I look to Popper, Kuhn, Hull, Toulmin, and Blute & Armstrong for
exemplars of evolutionary theories of scientific change. Although each author relies on
evolutionary theory to a varying degree, evolutionary theory is well-suited to explain change in
science and the mechanism by which it occurs: descent with modification and natural selection.
‘Reports of the Death of the Sociology of Science Have Been Greatly Exaggerated’ is a
quantitative investigation of the output of the sociology of science and its relationship with other
research programmes in science studies. Recent statements about the decline of the programme
motivate the paper but conversely I find that the sociology of science is not in decline or being
outcompeted in the science studies environment. Though the environment is growing –
exemplified by the emergence of new research programmes - the sociology of science is
maintaining its distinctiveness.
‘The Evolution of Research Programmes: An Author Co-citation Analysis of Science Studies,
1949-2011’ is a principle component analysis of the structure of science studies using co-citation
data of the major authors in the field. I detail the nature of each component that is derived for
three time periods and explain the patterns of interaction between the groupings of authors.
There are two findings of interest: 1) methodological and 2) substantive. Methodologically I find
that author co-citation analysis from journal articles produces a “messy” portrait of science
studies. Research programmes – or authors’ self-use of these labels - does not accurately map the
substantive composition of the field. Substantively I find that the environment and the density of
authors/programmes in these environments is increasing through time. The nature of the
diversification of science studies is also characterized by conflict, competition, and cooperation
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and each is evident in the substantive contents of each component. I synthesize this evidence in
conjunction with the findings of the previous papers using evolutionary theory and I recommend
future areas of research.
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Chapter 2 Unraveling Scientific Development: Sociocultural Evolutionary Theories of Science as a Process.
1 Evolutionary Theory and Cultural Change
The application of evolutionary theory to sociocultural topics is not new. Baldus, for example,
uses evolutionary theory to explain the emergence and maintenance of social inequality
(Personal Communication, 2011). Similarly, Currie et. al (2010) employ phylogenetic methods
to trace changes in political complexity in South-East Asia and the Pacific. They find that a
sociocultural evolutionary approach to the development of hierarchical political organizations is
supported by statistical data. Basalla (1988) offers an evolutionary account of technological
development (artifacts) that focuses on the selection of traits based on their different fitness
relative to political, economic, military, etc. conditions. Aspects of Darwin’s theory have also
influenced social theory. For example, Karl Marx is said to have modeled his stage-theory of
historical development after aspects of Darwin’s evolutionary theory. Similarly, Durkheim’s
shift from mechanical to organic solidarity contains a natural progression in the form and
complexity of society (Toulmin, 1972). In a 1999 article, Hussey argues that aspects of
evolutionary epistemology and evolutionary theories of science reflect fundamental
misunderstandings of Darwin’s theory. In this paper I review evolutionary accounts of the
development of science/scientific knowledge and assess their strengths. A review of research
exemplars proceeds according to how explicitly they rely on evolutionary theory, from most
basic to the most explicit. I conclude by briefly situating these theories in the broader theoretical
literature of sociocultural evolutionary theory.
2 General Theories of Scientific Change
The study of science, scientists, and scientific activity proceeds along an interesting trajectory
due to the nature of the phenomena under study. It is said that reality is an ‘external’ reality
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waiting to be discovered and scientists are said to report observations of this objective reality
(Giere, 2006). Toulmin states: “the business of science (it was thought) is to study the causes of
natural phenomena; whereas science itself, as a rational activity, presumably operated on a
higher level, and could not be thought of as a “natural phenomenon” (1967, p.456). This
conception of scientific knowledge as somehow unique or different is increasingly challenged by
various theoretical developments in science studies. Price’s (1963) groundbreaking statistical
analysis of scholarly output brings scientific activity itself into the purview of analysis and
frames it as an output of human activity. Kuhn’s (1962) ‘revolutions in science’ identifies
paradigms (and paradigm shifts) as central analytic concepts while Merton’s (1937, 1942)
functionalist sociology explains science as a social institution and introduces the norms of
communalism, universalism, distinterestness, originality, and skepticism into science studies.
Woolgar and Latour (1979), in their laboratory studies, argue that external reality is constituted
by the tools we use to study it and it does not exist objectively but as objects of our
contemplation (1979). Shapin (1975), Collins (1993), Pickering (1995), and Giere (2006) all
argue that group interests, methodology, the research process, and instrumentation affect
scientific results and knowledge claims. Hess’ so-called third phase marks the dissolution of the
theoretical boundary between ‘discovery’ and ‘justification’ and the movement towards
sociological explanations of sociological knowledge itself (SSK), thus moving past the
Mertonian-Kuhnian approach towards a more “constructionist” approach (Hess, 1997;
Armstrong and Blute, 2010). More generally, Woolgar and Latour’s (1979) more general point is
that scientific facts are entities that are created, not simply observed. In terms of theorizing
science, so-called constructionist approaches generally hold grand narratives in disdain. However
Blute and Armstrong (2011) identify grand theories of science/scholarship offered by ten
contemporary sociologists or sociologically-minded philosophers and use interviews and textual
analysis to elaborate their similarities and differences on ten issues. One such approach is
evolutionary theory.
3 Scientific Change: Variation, Selection, Reproduction, Pattern.
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General theories of science conceptualize change in various forms, some of which resemble
those in evolutionary theory. Bunge (2003) makes the case for mergers in science among
different disciplines and research programmes. These mergers resemble hybridization in
evolutionary theory. Drori’s (2003) neo-institutional approach is a sort of evolutionary ecological
approach whereby institutions spread globally and each interacts with a slightly different
environment and takes on a ‘glocal’ form. Abbott (2001) finds a similar branching-type
development however he argues that a self-repeating cleaving or conflict results in a fractal
pattern. This type of branching is also shared by evolutionary theories of science however it
differs in key respects.
4 Primary Considerations
The evolutionary theorist Ernst Mayr (1988) argues that, contra Plato (and later Aristotle),
species cannot be expressed in nomothetic, necessary and sufficient terms. To do so is what he
calls ‘typological essentialism’. Instead he puts forth the notion of ‘populational thinking’:
species have many things in common but not necessarily everything (they are polythetic).
Proceeding further, for Hull (1988) and Ghiselin (1975) biological species are individuals (not to
be confused with organismic individuals). These individuals/entities are located in a specific
time and space. Popper, Kuhn, and Toulmin share this idiographic approach to species - the thing
that they describe (theories, scientific concepts) does not have an inner nature, an unchanging
nature, or an innate nature. These theorists take an anti-essentialist approach in their views of
scientific development.
Karl Popper (1959) (1972) famously set out to solve the ‘problem of induction’ and argued that
theory always precedes observation in the formation of knowledge. Like Hume, Popper believes
that it is a fallacy to establish natural laws (true theories) on the basis of repeated observation.
However, Hume proceeds further and argues that repetition is not a reasonable basis for
knowledge and yet it is a primary mechanism for our experience and knowledge of the world
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(custom or habit). “Even our intellect does not work rationally. Habit, which is rationally
indefensible, is the main force that guides our thoughts and our actions” (Hume, as cited in
Popper, 1997, p.95). For Hume human knowledge is irrational because rational people believe in
the validity of induction. This psychological aspect of the problem of induction is where Popper
breaks from Hume. Instead Popper seeks to accept the logical problem of induction while
maintaining human rationality (a psychological aspect). He performs this feat first by separating
the logical and the psychological aspects of the problem of induction. The central motivating
force in the development of knowledge is rational: criticism/dissatisfaction among practitioners
of existing theories. We reason rationally and act accordingly because our theories are based not
on induction but in accordance with reason. Justifying existing theories cannot lead to true
knowledge and instead science should strive to create theories that are falsifiable. Knowledge
starts from problems and develops because under scrutiny existing theories are bettered by new
theories that have a higher degree of precision and testability. We have rational reason to believe
our theories are true in a context of competing theories (Popper, 1972).
Kuhn (1962) largely agrees with these epistemic foundations and argues that observation is not
the basis of knowledge because both observation and measurement are conditioned by existing
standards and norms. Research is bound by tradition and more specifically it is bound by tools
and conceptual resources inherited from past generations. However, the act of discovery, for
Kuhn, is not exclusively conditioned by “external” factors. Epistemic factors form the basis of
scientific change and supersede the external conditions suggested by sociologists like Collins and
Ben-David (who focus on the effects of professions) and Price (concerned with the quantity of
scholarly output) (Wray, 2011).
Toulmin (1967) shares this assumption - exemplified in his desire to “show how a history of
ideas is related to a history of people” (p.459). What he means is that scientific development has
continuity both intellectually and in institutions. Whereas Kuhn and Popper are interested in
describing change according philosophical (read: logical) criteria, Toulmin situates the
production and selection of variation within the social sphere. “Scientists commonly take it for
granted that their criteria of “truth,” “verification,” or “falsification” are stateable in absolute
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terms” (Toulmin, 1967, p.463). The implication is that the system that produces and selects
among variations is socio-historical and a product of human activities. For Popper the historical
development occurs in accordance with logical principles (conjectures and refutation) (Toulmin,
1967; Devettere, 1973). These are the theoretical and logical bases on which each theorist
proceeds with their evolutionary theory of science.
5 Evolutionary Theories of Science
Evolution involves the selection of traits within a population that are recreated within a lineage.
A lineage resembles a tree with entities that have descended, with modification, from a common
ancestor(s) (Blute, 1997). Toulmin (1967, 1972) argues that Darwin’s ‘variation and natural
selection’ is in fact a general historical explanation that can be applied to other historical entities,
including science. Popper agrees and states “all this may be expressed by saying that the growth
of our knowledge is the result of a process closely resembling what Darwin called ‘natural
selection’; that is, the natural selection of hypotheses” (1979, p,261). One of the key components
of selectionist or evolutionary theory is random or blindly occurring variation in genetic material
every generation. In Darwin’s theory variation occurs prior to selection and is attributed to
mutation and recombination (Blute, 2010). These concepts have analogous ones in sociocultural
evolutionary theory. Kuhn and Popper appear to employ these evolutionary concepts in a way
that is more of an analogy whereas Toulmin, Hull, and Blute & Armstrong offer the most
‘faithful’ evolutionary accounts of the development of science.
5.1 Thomas Kuhn
Toward the end of The Structure of Scientific Revolutions (1970) Thomas Kuhn argues that
scientific knowledge develops in a fashion similar to how organic species evolve. His main
emphasis here though is epistemological as he seeks to take a developmental view of science
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whereby nature (and ultimate knowledge of it) is replaced as the chief aim of science (Wray,
2011). Instead science is driven from behind and not toward any fixed, external goal. More
precise conceptual tools continually replace old theories and tools as science becomes
increasingly specialized (Kuhn, 1970; Wray, 2011). As science develops its practitioners narrow
their scope which results in a branching pattern of an increasingly detailed conception of nature.
For Kuhn Darwin’s theory of natural selection and descent with modification is especially
relevant because Darwin sees a greater variety of species evolve. This is akin to Kuhn’s scientific
specialties. Furthermore, there exists a degree of continuity in the process of discovery as both
the problems scientists encounter and the conceptual tools they employ are previously developed
and inherited from predecessors. And like Darwin’s Principle of Divergence (Mayr, 1992) ,
Kuhn remarks that increasing specialization in science tends to restrict the interaction and
communication between different specialties as the refinement of their hypotheses, methods, and
tools has left them with less and less in common (1970).
5.2 Stephen Toulmin
Stephen Toulmin (1972) takes a populational approach to scientific change and uses a selection-
process to reconcile internalist and extrernalist theories. Rather than think of science in either-or
terms, Toulmin argues that the evolution of conceptual populations reflects a double-edged
process involving innovative factors (these represent variations) and selective factors (that
perpetuate favoured variants). He outlines four Darwinian commonplaces that are applicable to
conceptual development: 1) intellectual enterprises fall into ‘disciplines’ that contain their own
methodologies, concepts, and fundamental aims; 2) intellectual innovation is a continual process
that depends on (and is balanced by) critical selection; 3) ‘Forums of competition’ provide the
ecological conditions within which variations demonstrate their fitness; 4) “in any problem
situation the disciplinary selection process picks out for ‘accreditation’ those of the ‘competing’
novelties which best meet the specific ‘demands’ of the local ‘intellectual environment’”
(Toulmin, 1972, p.140; Nowotny, 1974). Selection is a communal affair that depends on a
common identification and agreement of the worthiness of novel suggestions to address
historically situated problems/puzzles. The notions of “testing”, “proving”, and “falsifying” are
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all intellectual goals of scientific disciplines within which the criteria of selection operate and
these goals are constituted in historical terms. Ideas are selected within disciplines if they meet
the demands of the situation (the external environment) better than predecessors. Conceptual
disciplines are historical entities characterized by growth and by intellectual and institutional
continuity. Given the interaction between variants and their local environment, the volume of
intellectual innovations largely reflects external forces. Mutation frequency directly links
conceptual development with organic development (Toulmin, 1972). Selection provides the basis
against which new innovations are measured and, if accepted, incorporated into the conceptual
‘gene pool’ to be ‘taken up’ by the younger generation of scholars in the master-pupil
relationship. Importantly, the vision of nature of each generation is never replicated exactly as
Toulmin argues this would be the sign of scholasticism. Instead, each generation re-creates their
vision of nature by combining the ideas they have encountered historically with the newly
incorporated variation.
Later intellectual cross-sections of a tradition reproduce the content of their immediate
predecessors, as modified by those particular intellectual novelties which were selected out in the
meanwhile – in the light of the professional standards of the science of the time (Toulmin, 1967,
p.466).
Toulmin invokes additional nomenclature from organic evolution in the case of new specialties
arising that have a unique history and genealogy (hybridization and cross-fertilization) and he
points to Abbott’s fractal model as a potential need to refine the evolutionary model.
Interestingly, Bunge concedes that patterns other than mergers are possible including
specialization and convergence and he compares these processes to biological hybridization (as
cited in Blute & Armstrong, 2011).
5.3 Karl Popper
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Popper is known for his philosophical approach to scientific development that is based on
conjectures and refutations. Science proceeds, according to Popper, not by attempts to support
and justify existing theories. Scientists create theories that are testable and refutable and when
tested and refuted results in theories of more accurate empirical content (Lakatos, 1968; Popper,
1979). Theories, in their development, assume a greater degree of universality and better
solutions to new problems. This improvement of new hypotheses over old ones is analogous to
comparative relative fitness (the chosen learning mechanism), for Popper. “The fittest hypothesis
is the one which best solves the problem it was designed to solve, and which resists criticism
better than competing hypotheses” (Popper, 1979, p.264). It is systematic criticism that
determines what theories are unfit and hence eliminated (Popper, 1979). Systematic criticism
goes hand in hand with trial and error learning and provides an opportunity to explain creative
thought in a non-teleological, deterministic fashion (Campbell, 1988; Popper, 1979). The pattern
of evolution varies according to the nature of science being considered. Applied knowledge and
human technology takes a form similar to organic evolution: increased branching through time
corresponding to increasingly specialized differentiated hypotheses (Popper, 1979). However,
the branching pattern of pure knowledge is different from organic evolution. Despite the
differentiation of problems pure knowledge tends to integrate into more general theories with
greater explanatory power. Popper argues that, unlike organic evolution, pure knowledge is like a
series of disconnected branches that converge over time. This tendency, he argues, stems from
the aim of scientists to develop better explanatory theories and to employ rational criticism to
find better theories. True theories here means they serve a better role in criticism and
eliminating unfit explanations (Popper, 1979). The difference in the direction of branching is
based on the level of interaction between hypotheses in scientific fields. This pattern is also
evident in organic evolution. Blute (2010) states, “branchings and mergers are about the absence
or presence of sexual interaction while diversification and convergence are about the absence or
presence of similarity” (p.42). For Popper, mergers occur when there is more social interaction
between practitioners and branching results when hypotheses are differentiated (read: they no
longer interact).
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5.4 David Hull
David Hull (1988) proposes an explicitly evolutionary theory of scientific change that
encompasses branching (Abbott, 2001; Drori, 2003), stability (Collins, 1998), convergence
(Bunge, 2003) and linear development (Ziman, 2000; Fuller, 2006). Hull seeks to build upon his
conceptualization of the selection process as a function of both interactors and replicators. A
replicator is defined as “an entity that passes on its structure largely intact in successive
replications” (Hull, 1988, p.408). An interactor is defined as “an entity that interacts as a
cohesive whole with its environment in such a way that this interaction causes replication to be
differential” (Hull, 1988, p. 408). Lastly, replicators and intercators function together in
selection: “a process in which the differential extinction and proliferation of interactors cause the
differential perpetuation of the relevant replicators” (Hull, 1998, p. 409). With these definitions
in mind Hull is able to analyze the structure of science and scientific ideas as a selection process.
For Hull, the substantive elements that exist in science function as replicators in conceptual
change. Thus, everything from beliefs about the goals of science to the appropriate ways to go
about realizing those goals is a replicator. Scientists share ideas that are identical by descent and
then are often recombined. This is facilitated by the coincidence of the scientists’ career goals
with the manifest goals of scientists. In this respect, the desire to gain credit among the scientific
community is a prime mechanism in conceptual selection. Credit is a key aspect of the reward
structure that scientists are embedded in and interacts with a system of trust and cooperation to
produce the distinct feature of science (Godfrey-Smith, 2010). This leads to concurrent
mechanisms including testing/checking and curiosity (Hull, 1988). Checking is a mechanism that
results from the fact that all publications (a vehicle) are based to some extent on previously
existing knowledge. Thus all scientific findings must be testable (but not necessarily tested).
Throughout the credit/checking process, ideas are subject to competition and relate to each other
as lineages. In this case, lineages may be conceived of as research programmes/theories – all
entities that are historical and located temporally and spatially. The scientists that interact within
these lineages may function as vehicles for replicators and intercators.
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Hull offers several significant theoretical insights that should be considered when studying
conceptual change. The first is the recognition that conceptual change is necessarily linked to
individuals that are historically situated, and thus the concepts may be analyzed as individuals.
This implies that any analysis of conceptual development in science must consider the role that
research groups play in influencing scientific ideas, thus identifying a social aspect of scientific
change. The second is Hull’s separation of selection into two component parts; interaction and
replication. This distinction ensures that conceptual selection will not be limited to preconceived
notions of replicator, interactor, and selection. This is exemplified in his example of a gene that
both replicates its genetic code and similarly interacts with its environment as a cohesive whole.
These key features of selection are then applied to conceptual change in science as Hull seeks to
identify interactors, replicators, and lineages in science. Lastly, Hull implores the reader to
accept his argument that empirical research and testing of hypothesis are critical components of
the evolution of scientific change. This includes replacing thought experiments with real
examples and introducing stronger methodological components.
5.5 Marion Blute & Paul Armstrong
Blute & Armstrong (2011) find that general theories of science/scholarship conceptualize change
in many patterns including branching, linear, merging, and converging. They argue that all of the
useful ideas in grand theories of scientific change can be incorporated in a Darwinian
sociocultural evolutionary theory. Evolution’s descent with modification handles all of the
patterns of change and novelty and repetition (including cyclical). Selection is a universal
mechanism that explains why, in any given context, certain ideas, theories, research
programmes, or methods spread or do not. Evolutionary theory also incorporates all of
competition, cooperation and conflict.
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In science, new environments both internal and external to the institution itself can restructure
old ideas, new ideas can reconstruct old environments, and sometimes both can even occur
simultaneously so that they mutually structure and construct each other - interact more or less as
Latour has it (Blute & Armstrong, 2011, p.422-423).
6 Debates and Criticism
Toulmin’s model shares many features with other thinkers though he tends not to agree entirely
with the accounts given by any. For example, Popper’s ‘conjectures and refutations’ (the
freedom of conjecture and the severity of criticism) are critical, says Toulmin, for “enhancing the
pool of conceptual variants” and “enhancing the degree of selective pressure” (1967, p.471).
Toulmin agrees with Popper that new variants are selected for incorporation in disciplines if they
have greater explanatory power than existing concepts. However, they differ fundamentally on
the philosophical basis of the standard by which a concept is deemed to be ‘better’. Toulmin
(1972), by locating the selection-criteria within scientific institutions, decouples rationality from
the realm of philosophy.
We must begin, therefore, by recognizing that rationality is an attribute, not of logical or
conceptual systems as such, but of the human activities or enterprises of which particular sets of
concepts are the temporary cross-sections: specifically, of the procedures by which the concepts,
judgments, and formal systems currently accepted in those enterprises are criticized and changed
(Toulmin, 1972, p.133).
By maintaining that rationality is part of a logical system Popper is employing a kind of
evolution geared toward some end goal. The notion of an ‘end goal’ is problematic in the realm
of sociocultural evolution because it suggests that selection occurs directly and is thus
Lamarckian (Hussey, 1999). Although mechanisms for the inheritance of acquired traits have
15
been theorized, it is largely accepted that adaptations must be heritable to be used in biological
evolution. However this is one of the general criticisms leveled against evolutionary theories of
science: the origin of variation in the sociocultural realm is not random or blind (Hussey, 1999;
Bryant, 2004). Bryant suggests that the biological account is flawed when it comes to culture
because “the socially constructed worlds of human agents constitute ‘environments’ of a rather
different order than the physical natural world that serves as the arena for biological struggle and
evolution” (2007, p.463). Therefore variation, fitness, and adaptability are all socially
conditioned entities (Bryant, 2004). In the realm of science, it is argued, innovations arise due to
pressures of the environment and they are designed purposely to avoid criticisms. Unlike a
Darwinian model, there is a sort of pre-selection in science that directs scientists’ activities
towards a presupposed goal (Hussey, 1999). This, Hussey argues, is precisely why a Lamarckian
process of evolutionary change is more appropriate when describing science than a Darwinian
one. The demands of the scientific environment direct variations and the mechanism for
producing change is direct and involves judgments about that same environment. However
evolutionary theory is historical. This is, as I’ve noted, perhaps the main underlying reason why
Kuhn and Popper are drawn to it. As such it incorporates historical contextual factors as
evidenced in Toulmin’s attempt to relate “a history of ideas to a history of people” (1972, p.459).
Second, evolutionary theory seeks to explain scientific development through evolutionary
processes that are historical, path dependent, and concern both the lived realm and inheritance.
This partially alleviates Bryant’s concern that: “it [biological colonization of the sociological
disciplines] through reductionist accounts [seeks to] explicate social phenomena as direct
phenotypical expressions of underlying biological or genetic factors” (2004, p.460).
7 Conclusion
I have demonstrated how a novel account of evolutionary theory makes sense of the development
of science. So long as an evolutionary account incorporates an historical analysis of historically
situated pathways, it transcends the boundaries between historical narrative and deterministic
causal theories.
16
Chapter 3 Reports of the Death of the Sociology of Science Have Been Greatly Exaggerated
8 Introduction: The legend
This title echoes Mark Twain who is apocryphally reported to have said that “the reports of my
death are greatly exaggerated” after his obituary was published in the New York Journal in 1897
while he was still very much alive. He died in 1910. His actual words “the report of my death
was an exaggeration” convey the famous sentiment, albeit a little less memorably1.
Here we report on another death which has been greatly exaggerated - that of the sociology of
science. According to a widespread legend, the sociology of science became extinct and was
replaced by one or more new modes of observing and theorizing about science. At the very least,
these new models are viewed as having been added to the mix and having come to dominate (e.g.
see discussion of Hess 1997, Yearley 2005, Sismondo 2008, and Restivo and Croissant 2008
below). The candidates usually mentioned are the sociology of scientific knowledge (SSK),
social studies of science, or social epistemology. Such legends are so widely believed in the field
most inclusively known as science studies2 that a prominent philosopher of science issued a
plaintive call for a revival of the sociology of science (Kitcher 2000). Similarly, Frickel and
Moore (2006) collected a series of case studies which they view as representing a revival of the
sociology of science, but one centered on the political. A related possibility is that the different
modes of studying science have become wholly distinct. Hull (2000) viewed this as undesirable
and called for more interaction, to be achieved by “cutting each other some slack”, an attitude he
viewed as prevailing in the study of Biology where philosophers, historians, social scientists and
even biologists interact in the International Society for the History, Philosophy and Social
Studies of Biology. So - it should be revived, it is being revived, it could be revived, but perhaps
first the question should be asked whether it ever died. Before some data is presented, an
extremely abbreviated history will be useful.
17
Originally, the philosophy, history, and sociology of science were independently institutionalized
(Hull 2000). Although metaphysics had long since evolved into the natural sciences and
epistemology into psychology and the social sciences, the philosophy of science for long
remained curiously immune to this ‘scientizing’ of what were once exclusively philosophical
topics. Eventually however, the reigning paradigm in the philosophy of science in the latter part
of the first half of the twentieth century, logical positivism, melted under Quine’s (1951, 1960)
attack on the analytic-synthetic distinction and his embrace of a (psychological) “naturalized
epistemology” (1969) as well as Kuhn’s (1962) historical account of revolutions in science.
These led ultimately to the conclusion that only theories as a whole have empirical import and
they, or more inclusively, paradigms or research programmes as a whole, only relatively, i.e. in
competition with others. In the view of some, these developments in philosophy led naturally not
so much to Popper’s (1959, 1962, 1972) falsificationism, his “conjectures and refutations”
emphasizing only selection against, but rather to “conjectures” and changes in relative
frequencies by means of any, or all of, competition, conflict and cooperation - i.e. to evolutionary
theories of scientific change such as those of Toulmin (1972) and Hull (1988). As a minimum,
they helped make space for the professionalization and institutionalization of the history and
sociology of science.
Some of Robert K. Merton’s writings on the subject of science date to the 1930's and 40's in
which he made it clear that he viewed the sociology of science as a branch of the sociology of
knowledge (e.g. Merton 1937) pioneered by Karl Mannheim. However, the sociology of science
was not fully institutionalized until the 1960's - primarily at Columbia University by Merton, but
also at The University of Wisconsin at Madison by Warren O. Hagstrom, and briefly at the
University of California at Berkeley by Joseph Ben-David (long associated with the Hebrew
University at Jerusalem). In addition to their own work (e.g. Hagstrom 1965; Merton 1973; Ben-
David 1971), each produced influential students (e.g. Lowell Hargens; Bernard Barber, Jonathan
Cole, Steven Cole, Harriet Zuckerman; and Randall Collins respectively). Although Merton’s
general thesis that scientists compete for status (“recognition”) rather than income, wealth, or
power, and his earlier articulation of the norms of the scientific community are the most widely
18
cited and quoted ideas from this body of work, the topic most extensively studied by this
‘school’ (in keeping with sociology at large of the time) was the determinants of social
stratification and mobility in science. What matters most for success - productivity, prestige of
the university of Ph.D. or status of mentor for example? The formal and informal organization of
the scientific community also received a great deal of attention. (On this general history see
Storer’s introduction to Merton 1973; Ben-David and Sullivan 1975; Cole 1992; Hess 1997:
Chpt. 3)
David Hess, who published one of, if not the first, pluridisciplinary text on science studies in
1997, laid out the historical narrative of science studies this way. He viewed the field as having
gone from i) the philosophy of science, to ii) Merton’s institutional sociology of science, to iii)
the strong programme of the sociology of scientific knowledge (SSK) which coalesced around
Edinburgh and Bath in the United Kingdom in the 1970's (e.g. David Bloor, Michael Mulkay,
Harry Collins, Barry Barnes) and finally to iv) “where the field is moving” - broadly labelled as
“critical and cultural studies of science” - including “anthropology, critical social theory, cultural
studies, feminist studies, critical technology studies, and the cultural history of science” (1997:
3). It is worth noting that, while Hess adopted the convention of labelling the earlier Mertonian-
style work as a different species so to speak, “the institutional sociology of science” rather than
just “the sociology of science”, he was among those who saw the new work as additions that
have come to dominate rather than to replace the older work (e.g. p. 84).
Moving to a more recent text (Yearley 2005) and very recent reviews (Sismondo 2008; Restivo
& Croissant 2008) we find some changes. For example, the earlier philosophy of science and
Merton’s “institutional” sociology of science tend to be more or less dropped from the narratives.
Hess’s account of where the subject was going in 1971 has become more differentiated. For
example Yearley identifies three “schools” in addition to the original Edinburgh one - Latour’s
actor-network theory; the study of gender and science; and ethnomethodology and discourse
analysis. Sismondo sees laboratory studies in general (including Latour and Woolgar 1979) and
ethnomethodology (e.g. Lynch 1985) as having succeeded the Edinburgh-Bath school, but sees
the main division currently (after Fuller) as being between a “high church” focused on science
19
and a more activist “low church” interested in technology and in making the latter accountable to
the public interest.
One of the things that Hess originally, and most later historians and reviewers of the changes
have agreed on, is that post-Mertonian science studies became “constructionist” under the
influence of Bloor’s strong programme (and perhaps also under Collins 1985 “empirical
programme of relativism”). Feyerabend (1975, 1978) probably deserves more credit for the
change than he is usually given, perhaps because his “anarchic” views eventually became an
embarrassment to the field. In any event, Bloor (1976) is credited with making the first move by
arguing for a “strong programme” that, after Mannheim, again addressed the knowledge content
of science. (He took aim at Merton for being insufficiently knowledge-focused and excessively
institutionally-focused). The strong programme would be causal, impartial with respect to the
truth or falsity of a belief i.e be symmetrical in its explanation of both, and reflexive i.e.
applicable to itself. According to Yearley (2005: Chpt. 2), Bloor is the “symbolic heart”, and
Bloor and Collins laid down the “framing commitments” of what followed. The constructionist
metaphor was ubiquitous in the 1980s and 1990s according to Sismondo (2008: 14) and is the
“fundamental theorem” of the subject according to Restivo and Croissant (2008: 214).3
One thing these authors (and others) do not agree on is whether or not the post-Mertonian
research under discussion is sociology. Sismondo (2008) hardly mentions the word. At the
opposite extreme, Restivo and Croissant (2008) have no doubt that it is. They go so far as to
view social constructionism as the ultimate realization of the nineteenth century theories of
Durkheim, Marx, Weber, Nietzsche and Simmel among others (214). In between, Yearley
(2005) is obviously ambivalent. On the one hand Sociology does not appear in his title: Making
Sense of Science: Understanding the Social Study of Science. On the other hand, the text claims
that the book is “primarily for the benefit of a sociological audience” and states that its purpose
is to “ investigate and remedy the disregard for the sociology of science in social theory” (xiv).
This ambivalence is sometimes poignantly expressed, “Sociologists . . . they (or rather, we). . .”
(2005: 62). One thing that is clear however, is that as the “constructionist” theme took hold,
labels other than the sociology of knowledge and sociology of science appeared and began to
20
become common - not only the “sociology of scientific knowledge” but also slightly less
frequently “social studies of science” and “social epistemology”.
If these accounts tend to agree that the field became “constructionist” but disagree on whether
these new strains of science studies are in fact sociology, another feature that they all have in
common is a curious omission of any discussion or even mention of “scientometrics” (sometimes
but less commonly called the “science of science”). As Merton (2000) noted in his essay in the
Festschrift in honour of Eugene Garfield, while the Science Citation Index was designed as a
bibliographic retrieval system for science itself, Garfield quickly recognized that he had invented
a specialty-specific research tool in the sociology of science, one which Merton’s students
quickly began to make use of. Indeed, much of the research performed in the sociology of
science would have been impossible without it. An unusual fact about science studies is that the
mainstream journals (e.g. Social Studies of Science, Science Technology & Society, Social
Epistemology, Episteme: A Journal of Social Epistemology, and Science, Technology & Human
Values - the latter the official journal of the Society for Social Studies of Science) tend to be
dominated by qualitative research with the quantitative largely confined to its own journal,
Scientometrics - the reverse of the situation that tends to prevail in Sociology more generally.
However, there is no doubt that even a cursory inspection of Scientometrics founded in 1978
reveals that the bulk of research published there is sociology of science by any standard. For
example a recent issue (V79 # 3, June 2009) includes articles on the influence of a particular
author, the social links between two kinds of scientific organizations, gender differences in
research productivity, whether China is becoming a power in the social sciences and the
influence individuals have on the impact of the organization of which they are a part.
9 Data source and methods
In the light of the foregoing, we decided to ask some simple questions and methodologically, to
investigate the ‘new’ interdisciplinary study of science with the kinds of bibliometric data and
21
methods characteristic of the ‘old’. Data was collected from the Web of Science yearly from
1957 to 2007 on items including the following expressions in their titles, abstracts or key words:
“sociology of science”; “sociology of knowledge”; “sociology of scientific knowledge”; “social
studies of science”; “social epistemology”; and “scientometrics”4. The Web of Science is not a
perfect indicator of what academics are up to. It no longer includes books for example – but it is
the best source of quantitative data available. Moreover, there is no guarantee that individuals all
mean exactly the same thing in using one of these expressions. The idiolects of individuals are
each a little different, usages in different subcultures somewhat more so, and in dialects even
more so. However, if there were not at least statistical commonalities in linguistic reference, no
communication would take place. Academics might as well stop writing. Indeed, humans would
have never have invented language in the first place. Academics generally use keywords in
particular to express how they construct what they are doing and to signal such to others, thus
hoping to attract suitable readers.
Data for this project was collected from the Web of Science: a subsidiary of ISI Web of
Knowledge. The database was accessed online through our library where we searched three
citation indices: Science Citation Index Expanded (SCI-EXPANDED)--1900-present, the Social
Sciences Citation Index (SSCI)--1956-present, and the Arts & Humanities Citation Index
(A&HCI)--1975-present. Using the advanced search option, we employed the following search
string: TS=”name of research programme” OR TI=”name of research programme”. The most
significant details are that TS is an operator for topic (i.e. key words or abstract) while TI is the
operator for title. The use of quotation marks around the search terms returns only results that
use those exact words, and the OR statement searches for results that satisfy either condition.
Furthermore, the TI search string searches for the words as they appear within a publication title,
not necessarily the only words in the title. We also omitted articles from 2008 and 2009.
For social epistemology and scientometrics, we sorted the results by date and manually recorded
the publication counts by year. For the remaining research programmes, additional steps were
required. The significance of the word ‘of’ in their titles (sociology OF science, social studies OF
science, sociology OF scientific knowledge, and Sociology OF Knowledge) caused some
22
complications in the search process. The Web of Science will not, even if included within
quotation marks, limit its findings to exact phrases. Thus, a search for “sociology of scientific
knowledge” would also include sociology of knowledge in its results. In order to obtain only
those publications that contained the exact phrase, we exported the ‘full record’ of each record
into an HTML file that was then searched for the desired phrase as an exact phrase and counted
and then recorded, according to year.
To evaluate the overlap among expressions, we searched the HTML output of the “sociology of
science”. The first step was to search, and highlight, all instances of the sociology of science. We
then searched the document again, this time looking for each of the other research programmes.
To be counted, the publication record had to contain both “the sociology of science” and the
research programme in question. Publications that met this criterion were recorded manually by
year. The database was then searched again for each of the remaining programmes (individually)
and recorded accordingly.
10 Research questions and results
The questions asked and results are as follows:
10.1 Has the sociology of science become extinct?
The answer is a definitive no. With a fair amount of variability but an upward trend, the number
of papers in the Sociology of Science has increased from a single one in 1957 to a yearly count
ranging from 12 to 28 in each of the past five years (see Figure 1.)
23
10.2 Given that it has not become extinct, has the “sociology of science” continued to be dominated by its parent, the “sociology of knowledge”, or come to be dominated by newer offshoots - for example the “sociology of scientific knowledge”, “social studies of science”, “social epistemology”, or “scientometrics”?
The answer is a definitive yes for the former and a definitive no for the first three of the latter.
From the first instance of the sociology of science in 1957 publications about the sociology of
knowledge have outnumbered the former in 38 years and more generally by 210 publications
(470 to 680). However, the number of publications in the sociology of science has exceeded
those of the sociology of scientific knowledge, social studies of science, and social epistemology
in every year from 1957 to 2007 except for 8 years for the first two and 6 years for the third in
which they were equal, with the bulk of those being zeros for both in some early years. As well,
the overall totals for all years are 470 for the sociology of science, 98 for the sociology of
scientific knowledge, 93 for social studies of science and 87 for social epistemology. The
sociology of science has also dominated scientometrics in all but 7 years (overall totals 470 to
275). On the other hand none of those are paired 0's, and moreover 4 of the 7 years have been in
the last 5. This is suggestive of what may be a hint of the beginning of a trend for scientometrics
to displace the sociology of science.
Of course, none of these facts should be taken to imply that the field has not changed since
Merton. As these new approaches have been added, the sociology of science’ proportion of the
total number of articles has declined (see Figure 2). On the other hand, a more reasonable
comparison than pitting the sociology of science against the sum of all others would be to group
it with scientometrics as representing the more traditional sociological approach and grouping
the social studies of scientific knowledge, social studies of science and social epistemology
together as roughly representing the “newer, more constructionist” approach (the sociology of
knowledge is irrelevant here and was not included). When that is done the former dominates the
latter in every year except 6 early years in which both sums were zero (total for all years are 745
24
versus 278). Moreover that predominance of the traditional sociological approaches includes the
most recent 5 years (see Figure 3).
10.3 Whatever the appropriate description of the level of institutionalization achieved (e.g. topic, field, research programme, paradigm, discipline etc.), does the sociology of knowledge, sociology of science and the newer enterprises constitute distinct ‘species’ in the sense that they are socially isolated from each other and fail to intercommunicate (in the way that members of different biological species fail to exchange genes or speakers of different languages fail to communicate with each other)? Or, on the other hand, are they varieties of the same species?
We tried to answer this question in three ways. First, one indication that they have not become
distinct would be if their frequencies tend to rise and fall together and that is roughly what is
observed (see Table 1.) Correlations of their frequencies are high and the spread among them is
not great. The correlations are scattered across a range from a low of .33 between the sociology
of knowledge and scientometrics to a high of .83 between scientometrics and the social studies of
science. This tends to suggest that there are external forces acting on all of them which tend to
increase or decrease their frequencies together. Much of that however is made up of the long
term trend for all to increase.
The second approach is to consider conceptual overlap. To what extent are these descriptors in
titles, keywords, or abstracts found in the same or in different papers? To determine conceptual
overlap, the presence of competing expressions was searched for in sociology of science
publications. Again, the evidence is unambiguous. Conceptual overlap between the sociology of
science and others is minimal. The largest case of overlap is with the social studies of science -
since 1975 14 publications – a meager 3% of all publications described as sociology of science
25
and 15 % of all publications described as social studies of science. Similarly, since 1971 the
sociology of science has overlapped with the sociology of knowledge 13 times. This represents
2.7% of all sociology of science publications and an even smaller 1.9% of all publications
described as sociology of knowledge. The overlaps for social epistemology, scientometrics and
the sociology of scientific knowledge are even less – 1 and 0; 4 and 2; and 2 and 10 per cents
respectively.
There has been a small increase in the total overlap of expressions recently – from 21/470 or 4%
pre 2000 to14/143 or 10% for 2000 to 2007. In addition, in origin, there does appear to have
been a close dependency of the social studies of science on the sociology of science. The first 4
articles (published from 1975 to 1980) described as social studies of science are also described as
the sociology of science. It was not until 1981 that the first independent occurrence of the social
studies of science is seen. In fact, the fragile state of the new expression initially is evident in
1982 when the sociology of science is mentioned in 5 publications in the journal Social Studies
of Science, with no mention, outside of the journal title, of the social studies of science5. A
similar situation is not observed with the others. 13% of articles in the sociology of knowledge,
16% of articles in the sociology of scientific knowledge, 46% in social epistemology, and 10% in
scientometrics, were published independently, prior to their first co-occurrence with the
sociology of science. Therefore, with the exception of the social studies of science in origin,
these appear to have originated, and continue to exist, as separate species within science studies.
This fact is curious with respect to scientometrics in particular given the similarity of much of
what is done under the two descriptors but the existence of such ‘sibling species’ speaks to the
power of institutionalization in science as elsewhere in society. Scientometrics developed its own
society (International Society for Scientometrics and Informetrics) and journal (Scientometrics)
while the others tend to cooperate in 4S (Society for Social Studies of Science) and in journals
such as Social Studies of Science, Social Epistemology, Episteme and Science, Technology and
Human Values.
26
The third approach considers the extent to which sociology of science articles and traditional,
more constructionist articles are published in each other’s journals. The obvious first step in this
procedure is to define the parameters of the two types of journals. Our definition of sociology
journals was quite strict. We included journals that contained ‘sociology’, ‘sociological’ or
‘sociology of’ in their title in whatever language. General social science journals were excluded
as were a great many other kinds of journals. We made an exception for Social Forces which we
know is a journal in which the authors are virtually exclusively sociologists. For more
constructionist journals we included only journals focusing on the social aspects of science, the
most important of which were listed above and excluded journals ‘of’ rather than ‘about’ science
e.g. “Science” as well as the many journals in the history and/or philosophy of science. Our
results for all the descriptors come from a total of 391 different journals. 15% of sociology of
science and scientometrics articles (119/768) comes from sociology journals. Interestingly, 15%
(43/281) of all constructionist articles come from their respective journals (see figure 4).
According to our strict definition of what constitutes a sociology journal and a more
constructionist journal, it is obvious that neither more constructionist nor sociology of science
articles are disproportionately published in their own journals. Furthermore, as figure 4 shows,
neither group publishes extensively across the field in each other’s journals.
11 Conclusion
In summary, quantitatively, it is clear that in science studies, judged by practitioners own
designations of what they are doing, the sociology of science has not become extinct, it has not
come to be dominated by other research expressions, and despite the addition of new descriptors,
it has tended to maintain its distinctiveness. Obviously it is important to sociology that the study
of a topic or field so important to the modern world as science not disappear, and that the
sociological approach to it (e.g. Nakhaie 2007, Siler and McLaughlin 2008) not become
overshadowed nor completely lose its distinctiveness.
27
NOTES
1 Twain’s quote was contained in a scribbled note available in scanned form at
http://www.twainquotes.com/Death.html (access date: July 24, 2009).
2In this paper we ignore the important “technological” side of the subject. Hence we ignore
descriptors such as “technology studies”, “the sociology of technology”, “the sociology of
technical knowledge” and “social studies of technology” - “science in society” as it has been
called as opposed to “society in science”. We also ignore the parallel terms which include both
i.e. “science and technology studies”, “the sociology of science and technology”, “the sociology
of scientific and technical knowledge” and “social studies of science and technology”.
3 Constructionism in turn is commonly said to have its roots in Berger and Luckmann‘s The
Social Construction of Reality published in 1966. That claim with respect to origins is quite
tenuous. In 1976, Bloor neither mentioned “constructionism” nor cited Berger and Luckmann’s
book. Moreover, the disconnect makes sense in light of the fact that Berger and Luckmann’s
book was primarily about offering a micro alternative to the macro sociologies of functionalism
and conflict theory which were fighting it out in sociology at large at the time rather than
emphasizing social construction in the subjectivist/relativist sense the term tended to take on,
justified or not, in science studies.
4 Unfortunately several approaches that are to varying degrees prominent in science studies -
particularly actor-network theory, ethnomethodology and feminist studies of science do not have
descriptors commonly enough used which also differentiate their general use from their specific
use in science studies or science and technology studies to enable us to employ them in our
study. The one closest to having such a descriptor is “feminist science studies” but a preliminary
looked showed this usage to be numerically insignificant. Undoubtedly however many studies in
these genres are included in one or more of the three “constructionist” groupings that were
28
employed. An interesting footnote on the choice of descriptors is that recently adopted by the
appropriate section of the American Sociological Association. In attempting to be inclusive, they
adopted “Science, Knowledge and Technology” as their section title. However, in choosing such
a unique expression they have undoubtedly frustrated the goal of making their research more
visible. At the time of our searches there was exactly one item including this expression. In
retrospect, it would have been much wiser to use what are in fact the most inclusive descriptors
albeit not explicitly so i.e. “Science Studies” or “Science and Technology Studies”.
5 This finding appears to support Collins and Restivo’s use of the sociology of science and social
studies of science as synonymous terms (1983). However, the fact that 85 per cent of social
studies of science articles do not feature the sociology of science implies that they are different
programmes.
29
Figure 1: Sociology of Science Counts
0
5
10
15
20
25
30
1957 1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005
Year
Pu
blica
tio
ns…
..
Sociology of Science
30
Figure 2: Science Studies Publications - Proportionally
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
19
49
19
51
19
53
19
55
19
57
19
59
19
61
19
63
19
65
19
67
19
69
19
71
19
73
19
75
19
77
19
79
19
81
19
83
19
85
19
87
19
89
19
91
19
93
19
95
19
97
19
99
20
01
20
03
20
05
20
07
Yea r
Pr
o
po
r
ti
o
n
S ocial S tudies of S cience S ocial E pis temology S cientometrics
S ociology of S cientific K nowledge S ociology of S cience S ociology of K nowledge
31
Figure 3: Proportion of More Constructionist/Non-Constructionist Publications
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1957 1960 1963 1966 1969 1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005
Year
Proportion....
More constructionist non-constructionist
32
Table 1: Correlation of Publication Counts:
So
cia
l S
tud
ies
of
Sci
ence
So
cia
l E
pis
tem
olo
gy
Sci
ento
met
rics
So
cio
log
y o
f S
cien
tifi
c
Kn
ow
led
ge
So
cio
log
y o
f K
no
wle
dg
e
So
cio
log
y o
f S
cien
ce
Social Studies of Science 1
Social Epistemology 0.60887 1
Scientometrics 0.833738 0.752238 1
Sociology of Scientific Knowledge 0.710999 0.604261 0.668562 1
Sociology of Knowledge 0.359496 0.363653 0.334022 0.391429 1
Sociology of Science 0.736292 0.619874 0.707022 0.680096 0.636424 1
33
Figure 4: Proportion of Articles Published in Sociology or More Constructionist Journals
15%
11%
15%
5%
0%
2%
4%
6%
8%
10%
12%
14%
16%
Sociology of Science, Scientometrics
SSK, Social Epistemology, Social Studies of Science
Descriptor
Sociology Journals More Constructionist Journals
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Chapter 4 The Evolution of Research Programmes: An Author Co-citation Analysis of Science Studies, 1949-2011
12 Introduction
In a recent paper Armstrong and Blute (2010) report on the ‘death of the sociology of science’
and investigate its supposed demise using bibliometric data. This paper moves beyond research
questions that focus specifically on the sociology of science and instead analyzes trends that
underlie changes in research programmes in terms of the content of their leading theorists.
Formal research programmes form the basis of data collection. However the structure of the
research field (science studies) is represented using author co-citation analysis and factor
analysis. The research questions asked are: i) what is the level of conceptual variation in science
studies?; ii) has this variation changed over time?; iii) if yes, what accounts for this change and
its degree?
13 Sociology of Science and Theories of Scientific Change
There are many ways to conceptualize variation and change in studies of science. Collins and
Restivo argue that contemporary science studies may be characterized according to research
programme (strong programme, scientometrics, or laboratory studies) or in theoretical terms by a
focus on Marxian (scientist as workers) or Weberian (scientist as professional elite) inclinations
(1983). In his handbook of Science and Technology Studies David Hess (1997) argues that
science studies have transitioned through three phases and currently resides in a fourth. He
views the field as having gone from i) the philosophy of science, to ii) Merton’s institutional
sociology of science, to iii) the strong programme of the sociology of scientific knowledge
(SSK) and finally to iv) “where the field is moving” - broadly labelled as “critical and cultural
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studies of science” - including “anthropology, critical social theory, cultural studies, feminist
studies, critical technology studies, and the cultural history of science” (1997, p.3). Several
authors mark the move away from the philosophy of science. This speaks to the more finely
tuned distinctions within these phases that focus on the ‘context of discovery’ or the ‘context of
justification’ as the main cleavage that characterizes early science studies (and whose seeming
irrelevance now characterizes later science studies) (Leydesdorff, 1989; Dolby, 1971). Most
prominently Kuhn’s (1962) introduction of revolutions in science identifies paradigms (and
paradigm shifts) as being central analytic concepts while Merton’s (1937, 1942) functionalist
sociology of science introduced the institutional norms of communalism, universalism,
distinterestness, originality, and skepticism into science studies and explained science as a social
institution employing central concepts like status as important variables. Interestingly, Collins
and Restivo (1983) persuasively argue that despite their different employment by future authors,
Kuhn and Merton’s theories both view science as stable, functioning institutions: “Kuhn is not
only a Mertonian, but he is a Mertonian sans sociology” (p.190). Hess’ so-called third phase
marks the dissolution of the theoretical boundary between ‘discovery’ and ‘justification’ and the
movement towards sociological explanations of sociological knowledge itself (SSK), thus
moving past the Mertonian-Kuhnian approach towards a more “constructionist” approach (Hess,
1997; Armstrong and Blute, 2010). Bloor (1976) is widely credited with the introduction of the
strong program which then proliferated in the works of academics in Edinburgh and Bath
(Mulkay, Collins, Barnes). In general terms the strong program can be epitomized by its
commitment to reflexivity, causality, impartiality and, symmetry (Hess, 1997; Armstrong and
Blute, 2010). Finally, Sismondo (2008) and Yearley (2005) have diversified Hess’ ‘where the
field is heading’ to include such research programmes as actor-network theory and laboratory
studies (Latour and Woolgar, 1979; Knorr-Centina, 1981), ethnomethodology and discourse
analysis (Lynch, 1985), and studies of gender and science (Keller, 1985). In their own handbook
of STS Jasanoff et al (2001) describes four models of scientific change that are not based on the
grand works of preselected authors. Rather the models vary by their answers to six questions
(social and cognitive dimensions) about scientific development: i) science as rational knowledge;
ii) competition; iii) science as socio-cultural practice and; iv) extended translation. Most recently,
Blute and Armstrong (2011) identify grand theories of science/scholarship offered by ten
sociologists or sociologically-minded philosophers and use interviews and textual analysis to
elaborate their similarities and differences on ten issues. The issues of greatest significance for
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this paper include i) the nature and pattern of change, ii) the mechanism of change and, iii) the
unique ideas.
Blute and Armstrong (2011) find that general theories of science/scholarship conceptualize
change in four patterns: branching, linear, merging, and converging.2 Additional patterns include
extinction or a cyclical pattern. Abbott, Hull, and Drori all see the nature of change as a process
of branching. For Abbott, this occurs in a cyclical pattern he calls a ‘fractal cycle’ whereby
competition between ideas results in winners and losers and the division that caused the initial
split is recreated on a smaller scale among the winners. The final product largely resembles
branching from a common ancestral lineage. Hull also argues that the nature of change in science
is branching, but he argues that the pattern is evolutionary. Curiosity provides conceptual
variation and additional ‘checking’ and ‘credit’ represent selection and descent accordingly.
Drori’s ‘globalization of science’ argues that science is not uniformly practiced throughout the
world and that its ‘styles’ are ‘glocalized’. For example, ‘cutting edge’ sciences emerge in
nations that have the financial means to afford the requisite technology. So the ‘idea’ or culture
of science spreads around the globe but its enactment is determined in large part by existing
institutions. Ziman, and Frickel see science progressing in a linear fashion. For example, Ziman
argues that Merton’s CUDOS were appropriate for academic science but have come to be
replaced by the norms of PLACE3 in post-academic science. Frickel, meanwhile, proposes that
scientific change proceeds in a fashion similar to other social movements and offers the notion of
scientific/intellectual movements (SIMs) that encompass grievances, social structure, and
cultural aspects. These social movements among scientists lead to the emergence of new research
programmes that rise up and replace (or don’t) existing programmes. It is also possible that new
programmes may coexist with existing ones by carving out a specialized area of activity or niche.
Lastly, the philosopher Mario Bunge argues that science changes through emergence and by a
pattern of convergence. Emergence, for Bunge, is the only source of novelty in science and this
2 The authors emphasize emergence because the previous lines of thought do not cease to exist.
3 “Knowledge may not be made public, work is done on local technical problems, governed by a managerial
hierarchy, commissioned to solve specific problems, and the scientists is valued as a technical expert” (Blute and
Armstrong, 2011, p. 404)
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novelty emerges via “convergence” of previously unrelated lines of inquiry. The mechanism of
change is ‘rational selection’ by individuals and the entire process resembles biological
hybridization.
Broadly, Armstrong and Blute (2010) find that a Darwinian sociocultural evolutionary theory
can successfully incorporate all of the useful unique ideas that characterize contemporary grand
theories of scientific change. Novelty and repetition (cyclical) are handled by evolution’s descent
with modification; all of the patterns of change that result in novelty are contained by
evolutionary theory and selection is a universal mechanism that explains why different concepts,
theories etc. spread or do not spread in science.4 Do these patterns and mechanisms of change
accurately describe empirical data about science studies? This paper describes the evolution of
the content of science studies’ leading theorists with an eye towards understanding how and why
it has evolved.
14 Data Source and Methods
Data was collected from the Web of Science: a subsidiary of ISI Web of Knowledge. The
database includes five citation indices: Science Citation Index Expanded (SCI-EXPANDED) --
1899-present; Social Sciences Citation Index (SSCI) --1956-present; Arts & Humanities Citation
Index (A&HCI) --1975-present; Conference Proceedings Citation Index- Science (CPCI-S) --
1990-present; Conference Proceedings Citation Index- Social Science & Humanities (CPCI-
SSH) --1990-present. Within the advanced search option, the most significant details are that TS
is an operator for topic (i.e. key words or abstract) while TI is the operator for title. The use of
quotation marks around the search terms returns only results that use that exact term, and the OR
statement searches for results that satisfy either condition. The search string for the dataset was:
4 Theories of scientific change outside of sociology have been omitted for brevity (Bonaccorsi and Vargas, 2010;
McCain, 1984; McCain, 1986; Moody, 2004; and Shwed and Bearman, 2010).
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TS=("Actor Network Theory and Science" OR "Feminist Critiques of Science" OR "Feminist
Science Studies" OR "Science and Technology Studies" OR "Scientometrics" OR "Social
Epistemology" OR "Social Studies of Science" OR "Sociology of Knowledge" OR "Sociology of
Science" OR "Sociology of Scientific Knowledge" OR "Strong Programme") OR TI=("Actor
Network Theory and Science" OR "Feminist Critiques of Science" OR "Feminist Science
Studies" OR "Science and Technology Studies" OR "Scientometrics" OR "Social Epistemology"
OR "Social Studies of Science" OR "Sociology of Knowledge" OR "Sociology of Science" OR
"Sociology of Scientific Knowledge" OR "Strong Programme").
The Web of Science’s ‘Create a Citation Report’ feature provides a detailed breakdown of how
many times each publication in the search results was cited in every year. Publications were then
sorted using Excel according to year and author. The author’s publications and citations (if more
than one) were aggregated for each time period and the number of times each author was cited
was then calculated. Those citation counts were then compared against the mean author citation
rate for the time period and only those authors who were cited at a rate higher than the mean
were selected to be paired with the highly-cited authors from the other research programmes.
15 Author Co-citation Analysis
Author co-citation analysis (hereafter ACA) is a citation method used in scientometrics to
“investigate the nature of[structure and] changes in scholarly activity and associated changes in
the intellectual, social, or cognitive structure of scientific specialties” (McCain, 1984, p.351).
The main unit of analysis in ACA is the set of documents that co-cite the works of authors
selected for analysis. In ACA an author’s work is considered in its entirety as an oevre (White &
Griffith, 1981). Authors of interest are paired together and a frequency table is constructed that
features a raw count of the number of times that any of author A’s work is cited in the same
publication as any of author B’s (McCain, 1990; White, 1990a; White, 1990b). The frequency of
papers that cite pairs of authors form the basis of a similarity or proximity matrix because as the
39
number of co-citations increases, it is argued that the author’s work is more similar (Leydesdorff,
2006) (See component 2, 1979-93 for an instance where competition can lead to similarity in co-
citations). ACA provides the researcher with a data-driven view of the relationships between
authors and the structure of the field more generally5.
16 Selection of Authors
A key component of ACA is how authors are selected to map the structure of a research area.
Eom (2009) offers several insights ranging from purely objective to completely ad hoc. When
understanding the evolution of research programmes in science studies, authors whose work was
most cited in their respective programmes during the respective time periods were selected. This
entailed amalgamating authors’ citation counts for all of their works during the specified time
periods and determining the average citation count, per research programme, per period. Table 1
identifies the average citation counts for each research programme per period and the number of
authors whose cumulative work in that period was in fact higher than the average6. This criterion
was employed to recognize the divergent citation rates within different research programmes as
well as their different historical evolutions. As Table 1.1 shows, the number of authors included
in the co-citation analysis ranges in the three time periods studies from 31 in 1964-1978 to 60
authors in 1994-2011.7
5 See White &Griffifth (1981); McCain (White & McCain, 1998); and (McCain, 1984) for examples of ACA.
6 Please see table 1. Numbers in bold refer to the criteria used for author selection. Due to the increasing number of
authors and publications and citations in later years the criteria for selection was modified to include authors whose
work was cited at least as often as the average citation rate + 2 standard deviations from the mean. Blank cells refer
to the fact that no authors published papers using that research programme as a keyword, in their abstract, or in a
publication title during that time period.
7 Table 2 commences with the time period 1949-1963 however this period is omitted from the analysis because of
too few authors to create a proximity matrix.
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17 Proximity Matrix, Factor Analysis
This analysis employs the quantitative technique of factor analysis to map the evolution of
science studies and uses the statistical package SPSS. However, before it can be accomplished a
dataset of co-citation counts is constructed for every pair of authors selected for analysis in each
time period. The program BibExcel was used to create a co-citation matrix to be imported into
SPSS89
. Once in SPSS a principle component analysis for each time period was performed. A
principle component analysis (hereafter PCA) is a descriptive statistical tool whereby factors (or
components) are derived based on the subset of authors who load on it (McCain, 1990).
Furthermore, the PCA function also returns a component correlation matrix that identifies the
relationships between the factors that are extracted from the data. The main ideas of each of the
derived components for each time period can be found in Table 2. These main ideas are
themselves derived from a qualitative analysis of the authors’ works who load heaviest on each
component for each time period. The results are discussed below.
18 Findings: 1964-1978
A principle component analysis using the author co-citation counts from 1964 to 1978 results in
the extraction of 4 components with eigenvalues above 1. 10
Cumulatively these components
account for roughly 43 per cent of the variance in the data matrix (see table 2.1). The pattern
matrix seen in Table 2.2 reveals how authors load on each component. The table has been
8 Following Leydesdorff (2009), the matrix from BibExcel was not standardized using Pearson’s R coeeficient
because the data is already a proximity matrix.
9 For a detailed technical manual for using BibExcel please see:
http://www8.umu.se/inforsk/Bibexcel/ollepersson60.pdf
10 The criterion of considering factors or components with an eigenvalue greater than 1 is known as the Kaiser
criterion. This is the common standard used with principle component analysis for deciding which factors to include
in the analysis.
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simplified to only show scores for authors who load on each factor above ± .40. It is then the role
of the researcher to analyze the individual loadings and to assign meaning to each factor based
on the content of the authors who load heavily on it: generally above ± .70(highlighted).
In qualitative terms, the hidden theme that structures the first component is establishing the
theoretical and methodological pillars that underpin the application of the sociology of
knowledge to science. This specifically revolves around the significance of the logic of
justification in the philosophy of science and the logic of discovery in the sociology of science.
The first component for this time period explains roughly 43% of the variance and is comprised
of 10 authors. Each author, ultimately, is involved in situating the sociology of science in its
historical context and outlining (with different implications) the intimate connection of data and
methods as justification/plan for its future direction. This occurs differently for the different
authors. Cotgrove (1970), Dolby (1971), and Law (1974) weigh the heaviest on the first factor
and can thus be analyzed to define its main characteristic. At the broadest level Dolby highlights
the historical meandering between concerns about the logical validation of the outcomes of
science (logical empiricism) and the more sociological concerns with science as a process of
discovery (sociology of knowledge). Here he discusses the need to overcome Merton’s tacit
acceptance of the empiricists’ rational and objective methods and to adopt a more Kuhnian
approach that situates sociological factors within numerous stages of the very method of data
collection and scientific methodology. Such an approach, Dolby argues, allows for a synthesis or
‘cross-fertilization’ of sociology of knowledge and philosophy of science that maintains its
emphasis on the progression and objectivity of science while simultaneously accepting the role
of theory and situating knowledge production in historical terms. In other words Dolby presents
a justification for a new form of relativism in sociological studies of science that is consistent
with the theoretical tenets of logical empiricism. This form of relativism is incorporated into
Cotgrove and Law, who both seek to contextualize the scientific process in terms of the social
processes involved in the creation and acceptance of norms and values by members of the
scientific community. Cotgrove explicitly describes science as a social activity and situates
scientists’ behaviour in a particular social context involving members of a community who seek
recognition of creativity. Law similarly does not take norms for granted and argues that
understanding cognitive consensus among scientists would benefit from including theoretical
42
tools from a social-psychological interpretative approach. This approach allows one to
investigate the empirical building blocks of norms and paradigms and to make connections
between methods, theories, and this data.
The specific contributions of the three authors presented above correlate highly with the first
component due to their broad concern with theoretical matters Undoubtedly Robert Merton
(1972) also correlates highly with this factor, though a closer analysis of his work from the
period suggests that it correlates because of its more general sociological treatment of knowledge
which the remaining authors both build on and ultimately transcend as they apply it more
concretely to science as a particular field of knowledge production. Thus, the remaining authors
who correlate highly with the first factor are similarly concerned with the emerging theoretical
bases of sociological studies of science, but are also involved in testing these theoretical
assumptions against empirical examples. Clarke (1968) and Mulkay (1974) explicitly begin their
works by emphasizing the intimate connection between sociological factors, theoretical
predispositions, and ultimately, substantive results.
The underlying structure of the second component [accounts for approximately 21% of the
variance] is exclusively centered on the sociology of knowledge and, unlike the first component,
focuses no attention on science as a specific form of knowledge. A brief look at the authors who
load heavily on this component shows concerns with the problems of relativism for teaching
(Young, 1973), an application of the sociology of knowledge to interpret terminology systems
(Mckinley, 1971), and an attempt to integrate Gramscian concepts of ideology and hegemony
within a Marxian sociology of knowledge (Salimini, 1974). Clearly the works of these authors
represent developments within the sociology of knowledge that are both theoretically and
substantively concerned with sociological issues other than science. Curtis (1970) and Fischer
(1966) also weigh heavily on this component and their work correlates strongly with the theme
of the application or refinement of the sociology of knowledge to community power research
(Curtis) and trends in Soviet sociology (Fischer).
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The common theme that the third component discovers in the data is one concerned with the
theoretical and methodological consideration of micro and macro levels of analysis for
sociological studies. Only two authors correlate uniquely and highly with the third component
extracted from the co-citation data and it explains roughly 10% of the variance in the data. This
component is exemplified by the works of Manis (1968) and Berger (1966). In his work on
community health research Manis dissects the central concepts and theories using the sociology
of knowledge to highlight extra-theoretical influences. For example, he argues that the absence
of community-centric theories within the field has consequences for the validity and reliability of
operationalization of the central topics including community and mental health. He also argues
that the inductive approach employed by researchers in the field must recognize that sociologists
are acted upon and influenced by specific groups and play an active role in the choice of theory
and methodology. Berger (1966) continues with the theme of individual identity and accounting
for the individual in the sociological endeavor with his critique that the sociology of knowledge
has not (and should have) been integrated with the social psychology of George Herbert Mead.
He argues that while the sociology of knowledge implicitly recognizes the role of subjectivity in
the creation of knowledge, there is no explicit recognition of how individual reality is socially
constructed. Social psychology is a useful tool for understanding how an individual is situated in
a social milieu and what effect this dialectical relationship between self and social structure has
for objective reality and internalized identities, or between objective and subjective aspect of
reality.
Manis concerns himself primarily with problems of aggregation when defining sociological
concepts such as community or mental health and the use of population characteristics (which
are mere aggregates of individual level data rather than socio-cultural variables) in community
health research. In a different way Berger is also concerned with micro level aspects of the
sociology of knowledge. Where Berger differs from Manis however is in his desire to
incorporate social psychological theory into the sociology of knowledge to provide a more
nuanced theoretical proposition about the active role of individual cognition and social structure
which interact to create objective and subjective reality which are internalized and reproduced.
Both authors argue that there are theoretical and conceptual shortcomings of ignoring the dual
44
nature of consciousness (Berger) and sociological research (Manis) and research must consider
multiple levels of reality to be valid and to give reliable accounts.
Lastly for this time period, the fourth component extracted from the data explains approximately
5 per cent of the data and is exemplified by Walton who is the only author that loads heavily on
the component with no cross-loading across categories. Walton’s (1966) work provides the
empirical basis of papers that followed temporally by Clarke (1968), and Curtis (1970). This
work is noted for its reference to sociological factors as being ‘variables’ and is largely a
descriptive account of the temporal ordering of research disciplines, research methods, and the
outcome variable of interest (community power structure as conceived by researchers).
Interestingly, two prominent authors (Ben-David, 1970 & Garfield 1971; 1978) load heavily on
the first and fourth factor; a feature that helps to explain the slightly greater positive correlation
(.443) between these factors1112
. Garfield’s correlation with the first component demonstrates his
concern with the history of science as a substantive area and his concern with theoretical and
methodological challenges to his citation index. However, his strong correlation with the fourth
component reflects his acceptance of methodological challenges to bibliometric work and his
clear commitment to minimizing those challenges and enshrining citation data for the social
sciences and science studies into his bibliometric datasets. Finally, Ben-David’s (1970; 1975;
1978) oeuvre for the period correlates strongly with both the first and fourth component in large
part because of the historical focus of his work. Thus when Ben-David traces the pre-World War
2 developments within the Sociology of Knowledge he is actively identifying how theoretical
and methodological variations resulted from concrete historical events. However, concurrent
with this approach, Ben-David highlights the ways in which the social functions changed and
thus resulted in changes to the structure of science. His analysis focused largely on the effects of
11 Phillips also correlate strongly with the first and fourth component however he had a very strong correlation with
the third component which makes it difficult to categorize his relationship with the underlying themes in the dataset.
12 As discussed in the methodology section, rotation is a tool used to achieve a simpler structure of the data. Oblique
rotation assumes that there is a possible relationship between the underlying components in the data. The component
correlation matrix (table 3) shows that in fact all four of the components derived from the data are positively
correlated with each other however the correlations are weak.
45
these changes on the rate of scientific production: a substantive area that is well-suited to
analysis by means of bibliometric analysis as a representation of impact and future directions.
19 Findings: 1979-1993
In this time period there is an expansion in the overall size of the science studies community and
the emergence of new, distinct research communities. With the increase in authors and articles
since the previous period, it is no surprise that a principle component analysis extracts more
components from the dataset. Compared with 4 components for 1964-78, the PCA extracts 7
components with the cumulative ability to explain 86 per cent of the variance. Of particular
interest is the increased prevalence of the first latent factor (explaining 52% of the variance) with
a more equitable distribution of variance being explained by the following three factors (7.9%,
7.4%, and 6.8% respectively). Compared with the previous time period, the first four
components explain roughly the same cumulative variance (75% vs. 80%), however 3 additional
components are extracted that have eigenvalues above the critical value of 1 (see table 3.1). An
inspection of the component correlation matrix for this time period shows that all the extracted
components are positively correlated with each other to varying degrees. The first and second
components cumulatively explain 60% of the variance and are correlated strongly and positively
with each other (.712). In fact, the first and second components tend to correlate fairly strongly
with almost all of the extracted components. Of particular note though is the distinction between
the second and third component in terms of their correlation with each other and of the third
component’s correlation with other extracted factors. The second and third components explain
roughly the same proportion of the variance (7.9% and 7.4%). However they are not strongly
correlated with each other (.293), especially considering the strong correlation between the
second and fourth and fifth components (.519 and .610). This demonstrates an emerging,
independent component in the dataset that explains as much variance as other components that
are more closely related to the predominant structure or theme in the data (component 1).
Component 3 represents scientometric works that have moved beyond criticism and self-
justification and operate independently of the established themes within science studies.
46
The first component can be thought of as a collection of authors who comment on developments
within science studies away from Mertonian sociology of science yet offers distinctly
sociological interpretations. This is most telling in a new found emphasis on the importance of
conflict and competition in scientific practice. The first latent factor is characterized by the
following authors who load heaviest on it: Holzner (1.307), Kuklick (1.215), Bates (1.167),
Randall Collins (1.039), and Rollhansen (.983) (see table 3.2). Overall the first component
explains 52 per cent of the variance within the data; a fact reflected by the broad scope of the
authors who load positively and heavily on it. Holzner, for example, produced several articles
within the time period which laid out the special relationship between the sociology of
knowledge and the sociology of science. More specifically, Holzner (1982) analyzes, from a
sociological perspective, knowledge structures and different forms of knowledge utilization as
they are situated in practical enterprises. Secondly, Kuklick (1983) also focuses on the sociology
of knowledge and evaluates the research programme’s movement back to Mannheimian roots
and the greater incorporation of history and contextuality in sociology of knowledge research
(including science). Perhaps most representative of the overall theme of the first component is
Collins (1983) and Restivo (1987), who seeks to break down existing functionalist
interpretations within the sociology of science and move towards a theoretical toolbox equipped
with (especially) conflict, cooperation, and diversity. Other authors who load heavily on the first
component also reinforce a distinct sociological aspect either through critique on a broader
sociological basis (Delamont, 1987); a call to include sociological themes within the studies of
science (Restivo, 1987); or the construction of knowledge claims within sociologically-analyzed
settings (Tibbets, 1986). In all of these cases the authors demonstrate a willingness to move
beyond the Mertonian and the Kuhnian sociology of science and apply a more critical eye
towards the subject of analysis, be it in knowledge claims, theoretical issues of historicity, or
incorporating conflict into any analysis of science.
The second component extracted from the PCA explains 7.98 per cent of the variance in the data
and is strongly and positively correlated with the first factor (.712). Further inspection of the
component reveals that the overall theme in fact builds on the new critical aspect of the first
47
component. The second component deals almost entirely with constructivism in science studies.
The three authors who load heaviest on this factor include Leydesdorff (1.054), Radder (1.006),
and Winner (.967) and they share a common theme: they are critical of the constructivist trends
in science studies and they engage it directly. Conversely, many of the remaining authors who
load heavily on the component can be viewed as defending constructivism (Mulkay, 1979; 1981;
Smith, 1984; and Woolgar, 1988; 1991). Many of these authors also load above the .400
threshold on the first component and this clarifies the strong positive correlation between the first
and second component. The second component is primarily a critique of the current state of
science studies and authors who exemplify this approach (and characterize the first component)
are drawn out as exemplars for the field. It is thus clear that even argumentation is a form of
interaction.
The third component is perhaps the most telling indication of speciation within science studies.
This third component represents the emergence of a unique research programme in science
studies that appears to have gained independence from existing programmes and communicates
very little with them. It explains roughly the same variance in the data as the second component
(%7.49 and %7.98 respectively) yet for such a large component it correlates weakly with the
other three prominent components (see table 2.3). The weak correlation between the 3rd
component with the 1st, 2
nd, and 4
th is substantiated when looking at individual authors.
Compared to the first and second component, significantly fewer authors load heavily (above
.400) on the third component. This means that there is little interaction or communication
between these authors and others. Analysis of the three primary authors who load heavily on this
component clearly shows a new species: quantitative, scientometric analyses within science
studies. To be clear, discussion of scientometrics also figured prominently in the second
component, however, there it was still discussed in relation to the existing/dominant approaches
within science studies. The authors who load heavily on the third component have moved
beyond critique and make little to mention of sociological or constructivist approaches in their
work. The radioanalytic chemist, Lyon (1984, 1984b, 1985), loads heaviest on the third
component (1.058) because his work is both a reflexive account of a scientist about science
studies - his report from the annual meeting of the society for social studies of science (4S)
(1984) declares that he and his fellow scientists and engineers are the subject of sociological
48
analysis - and because he moves past critiques of sociology and presents a quantitative,
scientometric analysis of communication at scientific meetings. Lyon’s work loads negatively
and weakly with every other component derived from the data: he truly represents a novel
departure in science studies. Similarly, Lenoir (1979; 1979a) argues that co-citation analysis is
better suited than historical qualitative work at identifying the core literature within research
programmes and exploring the link between cognitive development and social development: a
characteristic of Mertonian Sociology of Science that has been lacking. Lastly, Moravcsik (1985)
and Lindsey (1980) both offer technical appraisals of scientometrics, though for different causes.
Lindsey approaches methodological problems in quantitative ‘counting’ methods of
scientometrics on their own ground and offer a resolution that remains firmly within the
quantitative sphere. Moravcsik goes further and explains how scientometric analysis can provide
indicators to measure scientific development in developing countries with an eye towards
measuring progress, activity, and productivity. The theme of this third component and its
relatively high share of descriptive power point clearly to a research programme that has evolved
within science studies and relies little on the substantive content of other programmes (or
components).
The fourth component extracted for the time period that explains more than 5 per cent of the
variance in the data is concerned with defending the traditional sociology of knowledge, or
rather, evaluating the efficacy of sociology of science theorizing for comprehending the
cognitive aspects of scientific development. This fourth component explains 6.85 per cent of the
variation in the data and only Harvey (.719) and Weiss (1.163) load heavily on it. Weiss (1987),
for example, analyzes social-psychological theories of values, attitudes, and beliefs within
organizational theory to determine whether their treatment of ideology serves as a suitable basis
for managerial decision making surrounding the treatment of alcoholism. He concludes that in
fact the over-reliance on ideology as a social-psychological term in organizational theory has not
been fruitful and that there is a need to incorporate social structure to expand understanding.
Harvey (1982;1987) defends traditional sociology of knowledge as well but unlike Weiss, his
targets are sociologists who have glossed over the theoretical intricacies of Kuhn’s notion of
paradigm and applied it, mistakenly, in contemporary sociological studies of science and
knowledge development.
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Prominent names in science studies load heavily on the 5th
component. Bloor (.459), Cozzens
(.478) and Delamont (.530) all load heavily on the component however David J. Hufford (1.197),
a Professor of (among other things) Folklore, weighs the heaviest. The fifth component explains
4.66 per cent of the variance in the dataset. The underlying theme of this component is, broadly,
a shared focus among the leading authors on the cognitive aspects of the sociology of science
and whether they are lacking in the current framework. Cozzens (1985) for example presents an
analysis of how citations to two specific scientific papers changed over time, and how it extends
beyond social structure. David Bloor’s (1982) discussion of Durkheim, Mauss, and the impact of
classification for systems of knowledge is highly relevant as he situates knowledge not only in
terms of being socially influenced, but being an influence as well. Finally Delamont (1987)
suggests learning environments and the socialization of scientists as one of the “blind spots” in
the sociology of science. Therefore, broadly, this component and its leading authors are largely
concerned with matters that transcend social structural concerns in the sociology of science, and
each looks to the cognitive practices of individuals for answers.
The use of Kuhnian paradigms is the underlying theme that best defines the sixth component
(3.48 per cent of the variance); however it is not as consciously employed by Domhoff (1.062) as
it is by Harvey (.649). Harvey (1982) explicitly challenges contemporary applications of Kuhn’s
paradigms in the sociology of knowledge. Conversely, though not explicitly, Domhoff’s (1987)
treatment of theoretical developments in the interpretation of the Social Security Act may be
interpreted as an attempt at a Kuhnian sociology of knowledge. Domhoff repeatedly uses
language as a metaphor to illustrate the disjuncture between various Marxian factions in their
treatment of important political acts.
The final component is represented by two authors whose focus is scientometric in both methods
and substance, and represent 3.16 per cent of the variance in the data. Yablonsky (.886) and the
founding father of the ISI, Eugene Garfield (.578), are the only two authors who load heavily on
the final component. Yablonsky’s (1985) contribution to Scientometrics is an extremely
technical analysis of the Zipf-Pareto law commonly employed in scientometric analysis.
Scientometrics itself is the topic of study. Garfield’s prominent contributions during this period
50
(1979; 1992) also characterize this component as they: 1) chart the history of scientometric
analysis and its institutionalization in the journal Scientometrics and; 2) an analysis of the
productivity and impact of Nobel laureates using citation counts. Interestingly, the final
component is correlated positively with the others from the period, however, it has a noticeably
weak correlation with the third component which is decidedly scientometric as well (see Table
2.3).
20 Findings: 1994-2011
As with the first two time periods, the first component extracted in the PCA explained a large
percentage of the variation in the data (51 percent). Furthermore, 27 authors load on the first
component above the cut-off of .400. It is not within the scope of this paper to comment on the
contribution of all 27 authors; however the contributing research programmes can be identified
before analyzing the heaviest loading authors (see Table 4.1 and Table 4.2 below).
There is great diversity in the research programmes that load heavily on the first component with
9 of the 11 programmes represented. However, the underlying theme that unites these authors
can be drawn from an analysis of the authors who load heaviest (see Table 4.3). In the case of the
first component the oeuvres of Berg (1.011), Marcus (.946), and Gherardi (.948) offer a glimpse
into the thematic aspects that bind these authors together and help explain much of the variation
in the data from 1994 to 2011.
The first component is built centrally, be it methodological or theoretical, around themes from
Actor Network Theory (ANT). For example, Marcus (1995) concentrates on the new movement
within science studies towards multi-cited ethnographic fieldwork. Gherardi (1999) and Berg
(1996; 2000) concentrate specifically on the notion of artefacts as they have been theorized in
ANT and apply it to theoretical concerns such as Organizational Learning Theory and the
51
sociology of knowledge or a new understanding of medical records and their role in re-
evaluating ‘representation’. These themes of representation, ethnography, and artefacts do not
only occur in the works of the top three authors. In fact, the next 6 authors who load heaviest on
this component all share a common concern with these themes. Whatmore (2000;2006) and
Murdoch (1997) speak at length of the ability of ANT to resolve dualisms in science and
technology studies between humans and non-humans and ascribe a creative role to such socio-
technologies. Other authors similarly discuss various aspects of ANT from a concern to applying
the results of STS research findings (Roth, 1996; 1997; 1998a;1998b, Demeritt, 1996; 2001), to
issues of ‘localization’ and politics as products of resolving dualisms that typified previous
theoretical approaches (Shapin, 1995; Slocum, 2004). What is clear is that the first component
derived from the data set represents a new trend in science studies; a trend institutionalized
largely in social geography and theorized in ANT. More than anything it demonstrates a concern
with new methodological questions and the theoretical implications of multi-site ethnography.
Lastly, this component focuses on applying the findings from STS research to either inform or
generate political events.
There is an unmistakable theme that unites the authors of the second component - Social
Epistemology. More specifically, and importantly, these authors concentrate on epistemic issues
surrounding library sciences, information sciences, and education. The second component
extracted from the PCA explains 9.86% of the variation in the data and compared to the first
component features a sharp reduction in the number of authors who load heavily on it (4). Don
Fallis, Alvin Goldman, and Thomas Uebel are the preeminent authors that load heavily on
component 2 (.903, .713, and .788 respectively). Fallis (2001, 2004) argues that social
epistemology is relevant for the information sciences because the decision of what materials to
include and exclude in a collection necessarily involve epistemic values and are necessarily
social because they are the material that forms a social connection between the provider and
recipient of knowledge. Goldman (2006) similarly applies social epistemological theory to
evaluate whether intelligent design should be taught in biology classes. Thus, social
epistemology is concerned here with evaluating educational practices in terms of knowledge
transmission and the identification of what constitutes experts and how they are to be involved in
curriculi (knowledge transmission) decisions. Lastly, Uebel (2000) is also concerned with
52
epistemic issues, though more so with the divide between logical empiricism and the sociology
of knowledge. Uebel argues that there is in fact the possibility of a middle ground between the
process of validation of scientific results (the domain of logical empiricists) and the context of
discovery (sociology of scientific knowledge). Component two is clearly representative of
[social] epistemological applications to questions of value theory and the sociological aspects of
knowledge transmission. Whereas these themes may also be generally covered by authors in the
first component, the specificity of the term social epistemology as well as only a passing
reference to science specifically serve as points of demarcation between component 1 and
component 2.
Component 3 is similar in certain respects to the second: it explains much less variation (5.86%)
than the first, and there are only 5 authors who load on it above +.400. Of these five authors three
load heavier than the rest and their work does well to help to identify the theme that unites them
and separates them from other authors. James Moody (2004) loads the heaviest on the third
component (.934) and his work deals with a sociological analysis of collaboration networks and
their effects on the scientific practice and the structure of ideas. This work loads heavily on the
third component in part because of its breadth: it employs counts of authors from sociological
abstracts to determine collaboration networks (quantitative, bibliometric techniques); its
explanandum is the content and structure of sociology and sociological ideas (SSK) and; its
explanans involves social interaction, typified through social networks. Vinkler (1996; 2000;
2004; 2007) loads heavily on the component (.843) and is also interested in eminence in science.
However, his concern is primarily around the technical aspects of scientometric indicators such
as the Garfield Factor and the h-index. In this respect he shares with Moody a concern for
questions of impact in science (Moody’s ‘area-authorities’) and he is similarly involved in
advanced quantitative methodology that maps the structure of research programme and
intellectual structures. Lastly, Leydesdorff (1997; 1998; 1999; 2007) loads heavily on the third
component (.833) in no small part because of his focus on tying bibliometric methodology
together with the theoretical aspects of social network analysis. Leydesdorff endeavours to map
communication networks using bibliometric indicators (co-citation, co-author, etc) to expand the
theoretical components of scientometrics.
53
If the third component of the PCA was involved in a sociologically-minded scientometric
analysis, then the fourth component is properly understood as scientometrics without the explicit
attention to sociological themes such as networks. The fourth component explains 4.44 per cent
of the variance in the data and contains 4 authors who load above .400. Of the four, the heaviest
loading belongs to the creator of the Science Citation Index and HistCite Software: Eugene
Garfield (.965). Garfield’s (1995; 1998; 2004; 2007; 2010) contributions can be conceived as
being largely institutional, introducing new technologies and methods in scientometrics. For
example, Garfield used his own HistCite software to situate himself in the evolution of
scientometrics; the publication activity of knowledge domain literatures; and reviews the
pragmatic role of scientometrics as a tool for research evaluation. Ying Ding (loading: .842)
similarly engages in bibliometric analysis and her work also engages in both methodology and
the application of said methodology. Ding’s (2000; 2001) speciality involves co-word analysis
and focuses on the field of information retrieval and the creation of more reliable datasets for
end-users of bibliometric analysis. Lastly, Martin Meyer’s (2000; 2004; 2010) research on
extending scientific citation analysis to studies of patent citations and his research on the
development of the emerging field of Computational and Mathematical Organization Theory ties
his oevre together with the empirical, scientometric theme that exemplifies the fourth
component. His loading of .703 is high and marks his role at the forefront of bibliometric
research.
The fifth component derived from the PCA explains 4.35 per cent of the variation and, like the
second, third, and fourth component, has a small number of authors who load on it over the value
of .400. Bruno Latour (.965), Neil Coulter (.737), and Loet Leydesdorff (.592) are the only
authors who load heavily on the extracted component and this is somewhat complicated by
Leydesdorff’s high loading on factor 3. What is particularly strange about this component is the
high loading of Bruno Latour and his low loading on the first component that was previously
described as being entirely ANT-related. However a closer look at the authors’ work in this
period shows that the fifth component is representative of a move towards greater
interdisciplinarity. For example, Latour (2000; 2002; 2003) variously argues that the current state
of sociology would benefit from modifications from STS. He goes on to argue that the late
theorists Gabriel Tarde is an exciting theorist for contemporary sociology given the discipline’s
54
shift towards psychologism, its importance for the sociology of science, and the breakdown of
the nature/culture divide. In other words, Latour has moved past the theoretical pronouncements
that underpin the work in component 1 but he takes those changes as given and is moving
sociology to a new direction. Coulter (1998) and Leydesdorff (1997; 1998; 2007) implicitly build
on this theme in their pursuit of interdisciplinarity. Coulter applies scientometric analysis (co-
word) to the field of software engineering to understand emerging and regressing trends.
Leydesdorff also focuses on scientometrics and attempts to bring it in line with sociological
theories of social networks and cultural evolution. He even explicitly seeks a theory-driven type
of scientometrics. This component is best described as one seeking interaction between different
research programmes with the aim of increasing the ability of both programmes to describe
social reality. This is a form of emergence by merger.
The sixth, seventh, and eighth components cumulatively explain 8.96 per cent of the variation in
the data (3.62, 2.71, and 2.63 per cent respectively) and cumulatively only have 5 authors who
load above .400 on them. Furthermore, components 6, 7, and 8 have very low correlations with
each other and with the remaining components. Black (.974) and Irwin (.482) weigh on the sixth
component and both figure in discussions on the history of information. Black (2006) relates this
information through a detailed historical analysis of the component parts of information history,
while Irwin’s (2006) discussion of new scientific governance and genetically modified food
involves the ways that information can be utilized to redefine public talk. Clemens (.896) and
Strauss (.928) are the only two authors who load heavily on the 7th
component and their work
can be collectively conceived as a sociological analysis of scholarly reputations as indicated by
publication histories. Clemens (1995) offers an empirical overview of differences between
gender, rank, and genre and how they relate to publication rates. Strauss (2008) no doubt
contributes to this theme through his own autobiographical account of his career in family
violence research. Here he offers observations that tie personal characteristics as well as
interactional characteristics to his own scientific career. Finally, Nettleton (.981) is the only
author who loads above .400 on the 8th
and final component. Her work in social epistemology is
strikingly similar to the work typical of the second component. She is interested in expert
knowledge and whether social policies relating to the internet and e-scaped medicine can
transcend structural inequality. No doubt the applied aspect of Nettleton’s (2003) work is what
55
distinguishes it from the work of the second component. Whereas those scholars were interested
in theoretical and epistemological questions pertaining to social epistemology and information
science, Nettleton’s analysis is decidedly more sociological in its inclusion of structural
inequality and real social policies.
21 Discussion
21.1 What is the level of substantive variation in science studies?
21.2 How has this variation changed in time?
The number of components derived in the PCA and the variation they each explain provide
important clues about the nature of variation that exists in any given time period. Recall that in
table 2.1 four components are derived from the data for 1964-1978. Together they explain 80 per
cent of the data. Interestingly, each of the second through fourth components explain half as
much variation as the previous one, despite relatively smaller declines in the number of authors
per component. For example, the first component explains 43 per cent of the variance and has ten
authors who load above .40 on it. The second component explains 21 per cent of the variance
and has 7 authors who load above .40. This, along with the weak correlations between the
individual components (see Table 2.3) suggests four relatively distinct substantive areas within
science studies with little intercommunication between them. This time period is also
characterized by a relatively dense environment. Across the four components 27 authors load
above .40 and explain a cumulative 80 per cent of the variance; this returns a density of 2.96.
By the time period 1979-1993 there appears to be an increase in communication with other
communities (see table 2.3). The overall density in the period is down to 2.04 as more
components are derived from the data (7) as well more authors (42) that load above .40 and a
slightly larger explained variance (86%). The change in value of the variance the second
56
component explains is particularly interesting in this time period. Whereas in the first time
period the second component explained roughly 20% of the variance and was weakly correlated
with the first component, from 1979-1993 the second component explains much less variance
(7.9%) and is quite highly correlated with the first, prominent component with a correlation of
.712 (see Table 3.3). Overall it appears that communication between the components
(substantive areas in science studies) has increased compared to the previous time period as
many of the components are positively and moderately correlated. This means that there is a less
discernible difference between the substantive bases of the components – merging. Rather what
may be occurring is in fact ‘minor tweaking’ of main ideas.
Lastly, from 1994-2011 the density again drops to 1.75 as 48 authors who load above .40 are
distributed over 8 components that explain 84 per cent of the variance. Consistent with the
previous time periods the first component explains much more variance than the rest (51 per cent
in this case). Furthermore, the component correlation matrix shows that other than a moderate
and positive correlation between the first and second component, no other components are even
moderately correlated (Table 4.4). The third through eighth components also explain less
variance than previous years and contain fewer authors who load above .40. So there is some
degree of similarity or communication between the practitioners of the first and second
component but by and large there is a degree of homogeneity within the data that was previously
missing.
21.3 What accounts for this change?
In simple descriptive terms, it could be argued that since 1964, more practitioners have written in
science studies but they are tending to do so more and more in the dominant substantive or
methodological paradigm. This would explain why, despite reduced density in each period, the
first and second components tend to be positively and strongly correlated with each other (and in
the middle years with other components). What was happening in each period that could explain
57
this? In the first time period the dominant component (that explains the most variance) is clearly
establishing the epistemological and ontological bases of the sociology of science, especially as
it relates to logical positivism and the philosophy of science generally. The second component,
unrelated according to the component correlation matrix, explains roughly 20 per cent of the
variance and is concerned primarily with matters pertaining to the sociology of knowledge with
no concern for science. So between the first and second component there is hardly a fine-grained
difference and instead the sociology of science, in general terms, carves out a niche for itself in
science studies that includes independence from the sociology of knowledge. The second time
period is a period of refinement as there is an influx of practitioners to the field but the field itself
has expanded from 4 to 7 components, thus reducing the overall density. In this period the
primary component (#1) explains more variance than it has in the past and it is strongly related to
3 other components that all correlate with it above .500. This is both a period of refinement and
of branching. The first component exemplifies the refinement of the sociology of science and the
firm identification of its roots. Highly related to this is the second component that, presumably,
accepts many of these foundations yet offers modifications which are substantively ones that will
usher in sociological accounts of scientific knowledge, or SSK. Thus the strong communication
between these factors does not necessarily signify agreement or cooperation, rather competition
and some conflict between substantive areas within science studies that were previously lacking.
This conflict is evident in the third factor, substantively identified as quantitative, scientometric
analysis, as it explains about as much variance as the second factor yet appears to communicate
very little with the other substantive areas. This represents speciation within science studies. The
final time period corresponds nicely with the assertions made by Hess (1997), Yearley (2005),
and Sismondo (2008) as there is variation. However, it has occurred within the primary
component. There is a substantial increase in the number of authors who load on the first
component (27) and they represent themes that encompass actor network theory, discourse
analysis, as well as ethnomethodology. Since this component explains 52 percent of the variance
in the data, this is truly the ‘where it’s heading’ of science studies. The lower overall density of
the time period (1.75) and the almost complete lack of interaction between the remaining 7
components suggests that the ideas espoused in the first component have eclipsed, and are not
dependent, on the ideas of the other components (or their historical relatives). In fact, as one
progresses down the remaining components there is a clear super-specialization that is occurring,
though this may be largely due to the inclusive nature of the first component. One might argue
58
that the fields occupied by the first component have a high carrying capacity. This means that it
contains much of the diversity that exists in the area and it has a high density.
22 Conclusion
As previously discussed, theorists have attempted to classify the evolution of science studies in
terms of research programmes. However this analysis has shown that in any given time period
several different approaches exist and the lines between them are anything but rigid. Research
programmes do not merely replace one another. Instead science studies evolve in a combination
of branching, convergence towards similar characteristics, linear development, and merging.
There is constant communication between scholars and research programmes though the nature
of this communication is not always clear. This finding is largely a consequence of the method
used to derive it. ACA (in this study) relies solely on journal articles. It is obvious that this
presents an incomplete look at the entire intellectual structure of science studies. Journal articles
may be more concerned with building upon the theoretical foundations that have been
established in books by prominent authors. Even the post-hoc sorting of material into schools or
programmes is likely to occur in handbooks and anthologies. This paper reports on the ‘mass’ of
output in science studies. We can expect that the distribution of authors who align on any issue,
substantive or methodological, will do so in a way that resembles a normal distribution. At the
two tails, or extremes, we should expect to find authors who either defend the position, or those
who attack it heavily and call for change. These are the authors I suspect would be represented in
books. However, the ‘mass’ of authors are those who mediate between the outliers. They are the
authors who apply the works of the ‘giants’ in the field to their own particular case. These are
authors who are less concerned with remaining at the forefront of the programme and instead
seek to fill new found space for publishing, attending conferences, and taking on new students.
The data presented in this paper are largely that middle ground. It shows communication in many
forms: competition, conflict, cooperation. It is balancing extremes to produce the greatest
conceptual variety with an eye to conceptual fitness. So, this analysis cannot argue that research
programmes are invalid for explaining the content of science studies. The evolution of ideas in
59
science studies in messy and any analysis that relies solely on a single representation of
academic output will miss telling the full story.
Table 1.1: Selection of Authors to Include in Factor Analysis: Mean citation count of authors by research programme and time period.
Table 2: The Main Ideas for Each Component by Time Period
1 2 3 4 5 6 7 8
1964-1978 Logical Positivism, Logic of Discovery
Sociology of knowledge, no attention to science
micro/macro considerations in science studies
variables' and the logic of inquiry
1979-1993 conflict, cooperation, diversity
constructivism: conflict and competition with existing paradigm
speciation: scientometrics
cognitive aspects of scientific development
the place of cognition in theory
Kuhnian paradigms
Methodology and institutionalizati on of scientometrics
1994-2011 ANY: ethnography, artefacts
Social epistemology: more epistemological at its core
Social networks: collaboration, communication, eminence
scientometrics Emergence centered on issues of 'information'
scholarly reputations: measurement and effects
social epistemology: at a very applied level
Component
Time Period
Table 2.1: Total Variance of Author Co-Citation Counts by Extracted Factors: 1964-1978*
Initial Eigenvalues Extraction Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative %
9.047 43.081 43.081 9.047 43.081 43.081
4.441 21.148 64.229 4.441 21.148 64.229
2.254 10.736 74.964 2.254 10.736 74.964
1.117 5.320 80.284 1.117 5.320 80.284
.848 4.040 84.325
*Extraction Method: Principal Component Analysis.
mean authors mean authors mean av+1sd authors mean sd av+2sd authors Actor Network Theory and Science 1.0 2.4 1 14.5 47.7 110.0 5 Feminist Critiques of Science 2.5 3.2 1 8.8 14.9 38.5 1 Feminist Science Studies 4.3 7.9 20.2 2 Science and Technology Studies 0.6 1.8 3 9.1 28.9 66.8 8 Scientometrics 1.8 1 5.1 20.0 5 7.2 19.4 46.0 9 Social Epistemology 0.0 0.3 1.0 4 3.5 5.9 15.2 7 Social Studies of Science 0.2 1 14.0 66.4 4 15.0 25.1 65.1 5 Sociology of Knowledge 0.1 2 1.5 23 0.8 3.8 13 6.3 17.7 41.7 10 Sociology of Science 2.2 1 1.2 6 2.4 9.0 10 8.6 28.1 64.9 7 Sociology of Scientific Knowledge 3.2 11.0 3 10.2 18.0 46.3 5 Strong Programme 1 1.6 2.3 6.2 1
Total: 3 31 45 60
1949-63 1964-1978 1979-1993 1994-2011
60
Table 2.2: Correlation between Authors and Components: 1964-1978*
Component
1 2 3 4
BendavidJ .446 .478
BergerP .566
ClarkT .822
ClinardM .694
CotgroveS .930
CurtisJ .758
DolbyR .867
FischerG .694
GarfieldE .531 .642
HorowitzI .408 .484
LawJ .965
ManisJ .757
MckinleyR 1.024
MertonR .771 -.640
MulkayM .657
PhillipsD .648 .649 -.447
PriceD .754
SalaminiL 1.024
WaltonJ .787
WarrenR .598 .437
YoungM .884
*Extraction Method: Principal Component Analysis.
Rotation Method: Promax with Kaiser Normalization.
a. Rotation converged in 7 iterations.
Table 2.3: The Correlation between Components: 1964-1978*
Component 1 2 3 4 5 6 7
1 1.000 .712 .364 .565 .606 .345 .432
2 .712 1.000 .293 .519 .610 .171 .401
3 .364 .293 1.000 .261 .346 .221 .319
4 .565 .519 .261 1.000 .522 .372 .298
5 .606 .610 .346 .522 1.000 .327 .402
6 .345 .171 .221 .372 .327 1.000 .252
7 .432 .401 .319 .298 .402 .252 1.000
*Extraction Method: Principal Component Analysis.
Rotation Method: Promax with Kaiser Normalization.
61
Table 4.1: Research Programmes and Authors Included in Component 1: 1994-2011
Actor Network Theory and Science Calas, Callon, Goodman, Murdoch, Whatmore
Feminist Science Studies Berg
Science and Technology Studies Brown, Irwin, Marcus, Sheller, Whatmore
Scientometrics Martin, Vinkler
Social Epistemology Bassett, Fuller, Garrison
Social Studies of Science Demeritt, Jasanoff, Murdoch, Roth
Sociology of Knowledge Gherardi, Olick, Scott, Shapin, Swidler
Sociology of Science Dasgupta, Callon, Long, Lynch
Sociology of Scientific Knowledge Barnes, Demeritt, Lynch, Roth, Shapin
Table 4.2: Total Variance of Author Co-Citation Counts by Extracted Factors: 1994-2011*
Component
Initial Eigenvalues Extraction Sums of Squared Loadings
Rotation
Sums of
Squared
Loadingsa
Total % of Variance Cumulative % Total % of Variance Cumulative % Total
1 23.097 51.327 51.327 23.097 51.327 51.327 22.688
2 4.439 9.865 61.192 4.439 9.865 61.192 10.542
3 2.646 5.879 67.072 2.646 5.879 67.072 5.155
4 2.000 4.444 71.516 2.000 4.444 71.516 5.251
5 1.960 4.355 75.871 1.960 4.355 75.871 3.578
6 1.630 3.622 79.493 1.630 3.622 79.493 2.302
7 1.220 2.710 82.203 1.220 2.710 82.203 2.126
8 1.185 2.634 84.837 1.185 2.634 84.837 2.044
*Extraction Method: Principal Component Analysis.
Table 4.3: Correlation between Authors and Components: 1994-2011*
Component
1 2 3 4 5 6 7 8
BarnesT .856
BassettK .690
BergM 1.011
BlackA .974
BrownN .888
CalasM .754
CallonM .898
ClemensE .896
62
CoulterN .737
DasguptaP .756
DemerittD .915
DingY .842
FallisD .903
FullerS .700
GarfieldE .965
GargK .644 .445
GarrisonJ .794 -.422
GherardiS .948
GoldmanA .713
GoodmanD .908
IrwinA .749 .482
JasanoffS .839
LatourB .765
LeydesdorffL .833 .592
LongJ .600 .420
LynchM .842
MarcusG .946
MartinB .495
MclaughlinN .469
MeyerM .703
MoodyJ .934
MurdochJ .938
NettletonS .981
OlickJ .586
RothW .936
ScottA .891
SecordJ .470
ShapinS .926
ShellerM .898
SlocumR .903
StrausM .928
SwidlerA .878
UebelT .788
VinklerP .843
WhatmoreS .939
Extraction Method: Principal Component Analysis.
Rotation Method: Promax with Kaiser Normalization.
a. Rotation converged in 13 iterations.
63
Table 4.4: The Correlation between Components: 1994-2011*
Component 1 2 3 4 5 6 7 8
1 1.000 .556 .260 .249 .137 .119 .110 .159
2 .556 1.000 .183 .090 -.055 .070 .037 .312
3 .260 .183 1.000 .407 -.072 -.037 .167 -.015
4 .249 .090 .407 1.000 .288 -.047 .024 -.003
5 .137 -.055 -.072 .288 1.000 -.019 -.075 -.061
6 .119 .070 -.037 -.047 -.019 1.000 -.140 .090
7 .110 .037 .167 .024 -.075 -.140 1.000 -.091
8 .159 .312 -.015 -.003 -.061 .090 -.091 1.000
*Extraction Method: Principal Component Analysis.
Rotation Method: Promax with Kaiser Normalization.
64
Chapter 5 Species of Science Studies
In his Science as a Process (1988) David Hull outlines the detailed history of the conflicts within
systematics in the 1970s and 80s between three competing schools of thought: numerical
taxonomy, evolutionary taxonomy, and cladistics. Each approach to ordering has distinct
characteristics and each has a different capability of dealing with homology and homoplasy. 13
These are traits that are derived from a common ancestor (homologous traits) and those that
result from convergence (analogous traits) (Blute, 2010). My research Species of Science Studies
implicitly uses two of the three schools of systematics and the third is an opportunity for future
research.
23 Numerical Taxonomy
Numerical taxonomy is a system of classification based on overall similarities and differences
between groups of organisms (Sokal & Sneath, 1963; Mayr & Bock, 2002). Reports of the Death
of the Sociology of Science Have Been Greatly Exaggerated (Armstrong & Blute, 2010) is a
numerical taxonomy of science studies. The sociology of science and other research
programmes are classified according to their overall fit using search criteria. There are necessary
and sufficient conditions for an article to be included as a member of a research programme
(taxon). I search for the name of research programmes in article keywords, titles, and abstracts,
and the resulting counts are groupings of how similar or different each article is with respects to
those criteria. A consequence of this taxonomy is that it is difficult to ascertain the evolutionary
relationship of the programmes because the taxonomic characteristics are decided in advance and
without in-depth analysis it is difficult to determine whether articles with shared characteristics
have done so because of common descent or convergence.
13 I follow Mayr & Bock (2002) and use the term ordering and not classification. Classification may be involved in
ordering nature but not necessarily.
65
24 Evolutionary Taxonomy
The Evolution of Research Programmes: An Author Co-citation Analysis of Science Studies,
1949-2011 relies implicitly on Ernst Mayr’s “biological species”. I derive the components for
each time period according to level of similarity and difference in co-citations – social
interaction analogous to genetic recombination. This is akin to interbreeding among authors. This
analysis produces a historical grouping of species (authors clustered into research programmes)
and the introduction of new species from groups of species. The varying social interaction
between research programmes yield new components in future time periods that differ from
those that they follow. Scientometrics is a strong case because we see it emerge in interaction
with the sociology of science and as it becomes more and more technical it ceases
communication with its ancestor.
25 Cladistic Analysis
Cladistic analysis has historical roots with the entomologist Willi Hennig who proposes that the
ordering of species must overcome the superficial similarities of numerical taxonomy. He
advocates a classification system based on historical similarities and differences (species ordered
based on a common descent). The result is a cladogram comprised of clades: “parts of a
phylogenetic tree” (Mayr & Bock, 2002, p.183). New taxa emerge from the process of
“budding” as new lineages separate from the parental ones. New branches now exist
independently from the parental line. Cladistic systematics is an area of future research for
species of science studies. I can specify morphological characteristics to organize citation data
and use cladistic software to produce cladograms. What should result, in combination with my
current findings, is a taxonomy of science studies that traces the historical evolution of the field
within its broader context (ecology).
66
References
Abbott, Andrew. Chaos of Disciplines. Chicago: University of Chicago Press, 2001.
Armstrong, Paul, and Marion Blute. "Reports of the Death of the Sociology of Science Have
Been Greatly Exaggerated." Canadian Review of Sociology 47 (2010): 431-44.
Barnes, Barry. "Social Life as Bootstrapped Induction." Sociology 17 (1983): 524-45.
Basalla, George. The Evolution of Technology. Cambridge: Cambridge University Press, 1999.
Bates, R. J. "Educational-Administration, the Sociology of Science, and the Management of
Knowledge." Educational Administration Quarterly 16, no. 2 (1980): 1-20.
Bendavid, J. "Emergence of National Traditions in the Sociology of Science - United-States and
Great-Britain." Sociological Inquiry 48, no. 3-4 (1978): 197-218.
———. The Scientist’s Role in Society: A Comparative Study. Chicago: University of Chicago
Press, 1971.
———. "Sociology of Science - Introduction." International Social Science Journal 22, no. 1
(1970): 7-27.
Bendavid, J., and T. A. Sullivan. "Sociology of Science." Annual Review of Sociology 1 (1975):
203-22.
Berg, M. "Practices of Reading and Writing: The Constitutive Role of the Patient Record in
Medical Work." Sociology of Health & Illness 18, no. 4 (Sep 1996): 499-524.
Berg, M., K. Horstman, S. Plass, and M. van Heusden. "Guidelines, Professionals and the
Production of Objectivity: Standardisation and the Professionalism of Insurance
Medicine." Sociology of Health & Illness 22, no. 6 (Nov 2000): 765-91.
Berger, P. "Identity as a Problem in Sociology of Knowledge." Archives Europeennes De
Sociologie 7, no. 1 (1966): 105-15.
Berger, P. , and T. Luckmann. The Social Construction of Reality: A Treatise in the Sociology of
67
Knowledge. Garden City: Doubleday, 1966.
Black, A. "Information History." Annual Review of Information Science and Technology 40
(2006): 441-73.
Bloor, D. "Ordinary Human Inference as Material for the Sociology of Knowledge." Social
Studies of Science 22, no. 1 (Feb 1992): 129-39.
———. "Knowledge and Reflexivity - New Frontiers in the Sociology of Knowledge -
Woolgar,S." Isis 81, no. 306 (Mar 1990): 155-56.
———. "Primitive Classification and the Sociology of Knowledge - Reply to Smith,J.W."
Studies in History and Philosophy of Science 15, no. 3 (1984): 245-49.
———. "Durkheim and Mauss Revisited - Classification and the Sociology of Knowledge."
Studies in History and Philosophy of Science 13, no. 4 (1982): 267-97.
———."Classification and the Sociology of Knowledge - a New Look at Durkheim and Mauss."
Kolner Zeitschrift Fur Soziologie Und Sozialpsychologie (1980): 20-51.
———. Knowledge and Social Imagery. Boston: Routledge and Kegan Paul, 1976.
Blute, Marion. Darwinian Sociocultural Evolution: Solutions to Dilemmas in Cultural and
Social Theory. Cambridge Cambridge University Press, 2010.
———. "History Versus Science: The Evolutionary Solution." The Canadian Journal of
Sociology 22, no. 3 (1997): 345-64.
———. "Reflections on Trees of Knowledge." Spontaneous Generations: A Journal for the
History and Philosophy of Science 3, no. 1 (2009): 223-25.
Blute, Marion, and Paul Armstrong. "The Reinvention of Grand Theories of the
Scientific/Scholarly Process." Perspectives on Science 19 (2011): 391-425.
Bonaccorsi, Andrea, and Juan Vargas. "Proliferation Dynamics in New Sciences." Research
Policy 39 (2010): 1034-50.
68
Bryant, Joseph. "An Evolutionary Social Science? A Skeptic’s Brief, Theoretical and
Substantive." Philosophy of the Social Sciences 34, no. 4 (2004): 451-92.
Bunge, Mario. Chasing Reality: Strife over Realism. Toronto: University of Toronto Press,
2006.
———. Emergence and Convergence: Qualitative Novelty and the Unity of Knowledge.
Toronto: University of Toronto Press, 2003.
Callon, Michel. "Four Models for the Dynamics of Science." In Handbook of Science and
Technology Studies, edited by Sheila Jasanoff, Gerald E. Markle, James C. Petersen, and
Trevor Pinch. 29-63: Sage, 2001.
Campbell, D. G. "The Author Responds: Popper and Selection Theory." Social Epistemology: A
Journal of Knowledge, Culture and Policy 2, no. 4 (1988): 371-77.
———."Blind Variation and Selective Retention in Creative Thought as in Other Knowledge
Processes." Psychological Review 67, no. 6 (1960): 380-400.
Campbell, D. T., P. Chapin, E. F. Infante, O. Larsen, J. Young, C. Kruytbosch, A. Morin, H. T.
Huang, and S. Cozzens. "Toward an Epistemologically-Relevant Sociology of Science."
Science Technology & Human Values, no. 50 (1985): 38-48.
Clark, T. N., W. Kornblum, H. Bloom, and S. Tobias. "Discipline, Method, Community
Structure, and Decision-Making - Role and Limitations of Sociology of Knowledge."
American Sociologist 3, no. 3 (1968): 214-17.
Clemens, E. S., W. W. Powell, K. McIlwaine, and D. Okamoto. "Careers in Print - Books,
Journals, and Scholarly Reputations." American Journal of Sociology 101, no. 2 (Sep
1995): 433-94.
Cohen, I. B. Social-Studies of Science - Barber,B. Current Contents. Vol. 9,1992.
Cole, S. Making Science: Between Nature and Society. Cambridge: Harvard University Press,
1992.
69
Collins, H. M. Changing Order: Replication and Induction in Scientific Practice. Thousand
Oaks: Sage, 1985.
Collins, Randall. The Sociology of Philosophies: A Global Theory of Intellectual Change.
Cambridge: Harvard University Press, 1998.
Collins, R., and S. Restivo. "Development, Diversity, and Conflict in the Sociology of Science."
Sociological Quarterly 24, no. 2 (1983): 185-200.
Colp, Ralph. Jr. "The Myth of the Darwin-Marx Letter." History of Political Economy 14, no. 4
(1982): 461-82.
Cotgrove, S. "Sociology of Science and Technology." British Journal of Sociology 21, no. 1
(1970): 1-15.
Coulter, N., I. Monarch, and S. Konda. "Software Engineering as Seen through Its Research
Literature: A Study in Co-Word Analysis." Journal of the American Society for
Information Science 49, no. 13 (Nov 1998): 1206-23.
Currie, Thomas E, Simon J. Greenhill, Russell D. Gray, Toshikazu Hasegawa, and Ruth Mace.
"Rise and Fall of Political Complexity in Island South-East Asia and the Pacific." Nature
467 (2010): 801-04.
Curtis, J. E., and J. W. Petras. "Community Power, Power Studies and Sociology of
Knowledge." Human Organization 29, no. 3 (1970): 204-18.
Delamont, S. "3 Blind Spots - a Comment on the Sociology of Science by a Puzzled Outsider."
Social Studies of Science 17, no. 1 (Feb 1987): 163-70.
Demeritt, D. "The Construction of Global Warming and the Politics of Science." Annals of the
Association of American Geographers 91, no. 2 (Jun 2001): 307-37.
———. "Social Theory and the Reconstruction of Science and Geography." Transactions of the
Institute of British Geographers 21, no. 3 (1996): 484-503.
Devettere, Raymond J. "Human Understanding. Volume 1.". International Philosophical
70
Quarterly 13, no. 3 (1973): 449-52.
Ding, Y., G. G. Chowdhury, and S. Foo. "Bibliometric Cartography of Information Retrieval
Research by Using Co-Word Analysis." Information Processing & Management 37, no. 6
(Nov 2001): 817-42.
———. "Incorporating the Results of Co-Word Analyses to Increase Search Variety for
Information Retrieval." Journal of Information Science 26, no. 6 (2000): 429-51.
Dolby, R. G. A. "Sociology of Knowledge in Natural Science." Science Studies 1, no. 1 (1971):
3-&.
Domhoff, G. W. "Corporate-Liberal Theory and the Social-Security Act - a Chapter in the
Sociology of Knowledge." Politics & Society 15, no. 3 (1986): 297-330.
Drori, Gili, John Meyer, Francisco Ramirez, and Even Schofer. Science in the Modern World
Polity: Institutionalization and Globalization. Stanford: Stanford University Press, 2003.
Fallis, D. "Epistemic Value Theory and Information Ethics." Minds and Machines 14, no. 1 (Feb
2004): 101-17.
———. "Social Epistemology and Information Science." Annual Review of Information Science
and Technology 40 (2006): 475-519.
———. "Social Epistemology and Lis: How to Clarify Our Epistemic Objectives." Canadian
Journal of Information and Library Science-Revue Canadienne Des Sciences De L
Information Et De Bibliotheconomie 25, no. 4 (Dec 2000): 42-42.
———. Social Epistemology and Lis: How to Clarify Our Epistemic Objectives. Beyond the
Web: Technologies, Knowledge and People. edited by D. G. Campbell2001.
Fallis, D., and D. Whitcomb. "Epistemic Values and Information Management." Information
Society 25, no. 3 (2009): 175-89.
Feuer, Lewis S. "The Case of the “Darwin-Marx” Letter: A Study in Socio-Literary Detection."
Encounter (October 1978): 62-67.
71
Feyerabend, P. Against Method. Brooklyn: Verso, 1975.
———. Science in a Free Society. New York: Schocken, 1978.
Fischer, G. "Current Soviet Work in Sociology - Note in Sociology of Knowledge." American
Sociologist 1, no. 3 (1966): 127-32.
Frickel, Scott , and Neil Gross. "A General Theory of Scientific/Intellectual Movements."
American Sociological Review 70 (2005): 204-32.
Fuller, Steve. The Philosophy of Science and Technology Studies. New York: Routledge, 2006.
Garfield, E. "Additional History and Sociology of Science Coverage in Current Contents."
Current Contents, no. 50 (1978): 5-8.
———. "Bernal,J.D. The Sage of Cambridge - 4s Award Memorializes His Contributions to the
Social-Studies of Science." Current Contents, no. 19 (1982): 5-17.
———. "Citation Indexing, Historio-Bibliography, and Sociology of Science." Current
Contents/Life Sciences 14, no. 15 (1971): M25-&.
———. "Cocitation Analysis of the Scientific Literature - Small,Henry on Mapping the
Collective Mind of Science - an Introduction to Macrolevel Changes in the Structure of
Cocitation Clusters - 1983-1989 by Small,Henry (Reprinted from Scientometrics, Vol 26,
Pg 5-20, 1993)." Current Contents 19 (May 1993): 3-13.
———. "From Citation Indexes to Informetrics: Is the Tail Now Wagging the Dog?". Libri 48,
no. 2 (Jun 1998): 67-80.
———. "From the Science of Science to Scientometrics Visualizing the History of Science with
Histcite Software." Journal of Informetrics 3, no. 3 (Jul 2009): 173-79.
———. From the Science of Science to Scientometrics. Visualizing the History of Science with
Histcite Software. Proceedings of Issi 2007: 11th International Conference of the
International Society for Scientometrics and Informetrics, Vols I and Ii. edited by D.
TorresSalinas and H. F. Moed2007.
72
———. "Historiographic Mapping of Knowledge Domains Literature." Journal of Information
Science 30, no. 2 (2004): 119-45.
———. "The Intended Consequences of Robert K. Merton." Scientometrics 60, no. 1 (2004): 51-
61.
———. "Kranzberg,Mel Receives Bernal Prize as Pioneering Historian of Technology - an
Introduction to Acceptance Speech of Kranzberg,Melvin - Jd-Bernal-Prize (1991) -
Society-for-Social-Studies-of-Science, Cambridge, Ma, Nov 14-17, 1991 by
Kranzberg,Melvin." Current Contents 13 (Mar 1992): 3-9.
———. "Measuring R-and-D Productivity through Scientometrics." Current Contents, no. 30
(Jul 1988): 3-9.
———. "New International Professional Society Signals the Maturing of Scientometrics and
Informetrics." Scientist 9, no. 16 (Aug 1995): 11-11.
———. "Price,Derek and the Practical World of Scientometrics." Science Technology & Human
Values 13, no. 3-4 (Sum-Fal 1988): 349-50.
———. "Science Historian Cohen,I.B. Reviews Social-Studies of Science by Sociologist
Barber,Bernard - an Introduction to Social-Studies of Science - Barber,B. By Cohen,I.B."
Current Contents 9 (Mar 1992): 3-7.
———. "Scientometrics Comes of Age." Current Contents, no. 46 (1979): 5-10.
Garfield, E., A. I. Pudovkin, and S. W. Paris. "A Bibliometric and Historiographic Analysis of
the Work of Tony Van Raan: A Tribute to a Scientometrics Pioneer and Gatekeeper."
Research Evaluation 19, no. 3 (Sep 2010): 161-72.
Garfield, E., and A. Welljamsdorof. "The Microbiology Literature - Languages of Publication
and Their Relative Citation Impact." Fems Microbiology Letters 100, no. 1-3 (Dec 1992):
33-37.
———. "The Microbiology Literature - Languages of Publication and Their Relative Citation
Impact (Reprinted from Fems Microbiology Letters, Vol 100, Pg 33-37, 1992)." Current
73
Contents 47 (Nov 1992): 6-10.
———. "Of Nobel Class - a Citation Perspective on High-Impact Research Authors."
Theoretical Medicine 13, no. 2 (Jun 1992): 117-35.
———. "Of Nobel Class - a Citation Perspective on High-Impact Research Authors (Reprinted
from Theoretical Medicine, Vol 13, 1992)." Current Contents 33 (Aug 1992): 5-13.
Gherardi, S. "Learning as Problem-Driven or Learning in the Face of Mystery?". Organization
Studies 20, no. 1 (1999): 101-23.
Ghiselin, Michael T. "A Radical Solution to the Species Problem." Systematic Zoology 23
(1975): 536-44.
Giere, Ronald N. Scientific Perspectivism. Chicago: University of Chicago Press, 2006.
Godfrey-Smith, Peter. "David Hull". Biology and Philosophy 25, no. 5 (2010): 749-53.
———. "Conditions for Evolution by Natural Selection." The Journal of Philosophy 104, no. 10
(2007): 489-516.
Goldman, A. "Social Epistemology, Theory of Evidence, and Intelligent Design: Deciding What
to Teach." Southern Journal of Philosophy 44 (2006): 1-22.
Goldman, A., and A. Grinstein. "Stages in the Development of Market Orientation Publication
Activity a Longitudinal Assessment." European Journal of Marketing 44, no. 9-10
(2010): 1384-409.
Goldman, A. I. "Argumentation and Social Epistemology." Journal of Philosophy 91, no. 1 (Jan
1994): 27-49.
———. "Social Epistemology." Critica-Revista Hispanoamericana De Filosofia 31, no. 93 (Dec
1999): 3-19.
———. Veritistic Social Epistemology. Proceedings of the Twentieth World Congress of
Philosophy, Vol 5: Epistemology. edited by R. CobbStevens2000.
74
Hagstrom, W. O. The Scientific Community. New York: Basic Books, 1965.
Harvey, L. "The Nature of Schools in the Sociology of Knowledge - the Case of the Chicago-
School." Sociological Review 35, no. 2 (May 1987): 245-78.
———. "The Use and Abuse of Kuhnian Paradigms in the Sociology of Knowledge." Sociology-
the Journal of the British Sociological Association 16, no. 1 (1982): 85-107.
Hess, David. Science Studies: An Advanced Introduction. New York: New York University
Press, 1997.
Holzner, B. "Special Issue - the Sociology of Knowledge - Introduction." Knowledge-Creation
Diffusion Utilization 4, no. 1 (1982): 3-6.
Holzner, B., and E. Fisher. "Knowledge in Use - Considerations in the Sociology of Knowledge
Application." Knowledge-Creation Diffusion Utilization 1, no. 2 (1979): 219-44.
Hufford, D. J. "The Supernatural and the Sociology of Knowledge, Explaining Academic
Belief." New York Folklore 9, no. 1-2 (1983): 21-29.
Hull, David. "The Use and Abuse of Sir Karl Popper." Biology and Philosophy 14 (1999): 481-
504.
———. "A Mechanism and Its Metaphysics: An Evolutionary Account of the Social and
Conceptual Development of Science." Biology and Philosophy 3 (1988): 123-55.
———. Science as a Process: An Evolutionary Account of the Social and Conceptual
Development of Science. Chicago: University of Chicago Press, 1988.
Hussey, Trevor. "Evolutionary Change and Epistemology." Biology and Philosophy 14, no. 4
(1999): 561-84.
Keller, Evelyn Fox. Reflections on Gender and Science. Yale University Press, 1985.
Kitcher, P. "Reviving the Sociology of Science." Philosophy of Science (Proceedings) 67 (2000):
S33-S44.
75
Knorr-Centina, Karin. The Manufacture of Knowledge - an Essay on the Constructivist and
Contextual Nature of Science. Oxford: Pergamon Press, 1981.
Kuklick, H. "The Sociology of Knowledge - Retrospect and Prospect." Annual Review of
Sociology 9 (1983): 287-310.
Kuhn, Thomas S. The Structure of Scientific Revolutions. Chicago: University of Chicago Press,
1962.
Lakatos, I. "Falsification and the Methodology of Scientific Research Programmes." In In
Criticism and the Growth of Knowledge, edited by I. Lakatos and A. Musgrave.
Cambridge: Cambridge University Press, 1970.
Latour, B. "Gabriel Tarde and the End of the Social." Soziale Welt-Zeitschrift Fur
Sozialwissenschaftliche Forschung Und Praxis 52, no. 3 (2001): 361-+.
———. "Is Re-Modernization Occurring - and If So, How to Prove It? A Commentary on Ulrich
Beck." Theory Culture & Society 20, no. 2 (Apr 2003): 35-+.
———. "When Things Strike Back: A Possible Contribution of 'Science Studies' to the Social
Sciences." British Journal of Sociology 51, no. 1 (Jan-Mar 2000): 107-23.
Latour, Bruno , and Steve Woolgar. Laboratory Life: The Social Construction of Scientific
Facts. Sage Publications Inc., 1979.
Law, J. "Theories and Methods in Sociology of Science - Interpretive Approach." Social Science
Information Sur Les Sciences Sociales 13, no. 4-5 (1974): 163-72.
Lenoir, T. "Perspectives in the Sociology of Science - Blume,Ss." Isis 70, no. 251 (1979): 152-
53.
———. "Quantitative Foundations for the Sociology of Science - Linking Blockmodeling with
Co-Citation Analysis." Social Studies of Science 9, no. 4 (1979): 455-80.
———. "Sociology of Science - Studies and Materials - German - Stehr,N, Konig,R." Isis 70,
no. 253 (1979): 447-48.
76
———. "Sociology of Science in Europe - Merton,Rk, Gaston,J." Isis 70, no. 251 (1979): 152-
53.
Lewontin, Richard C. "Gene, Organism and Environment." In Evolution from Molecules to Men,
edited by D.S. Bendall. Cambridge: Cambridge University Press, 1983.
Leydesdorff, L. "Caveats for the Use of Citation Indicators in Research and Journal
Evaluations." Journal of the American Society for Information Science and Technology
59, no. 2 (Jan 2008): 278-87.
———. "Configurational Information as Potentially Negative Entropy: The Triple Helix
Model." Entropy 10, no. 4 (Dec 2008): 391-410.
———. "Environment and Planning B: Planning and Design as a Journal: The Interdisciplinarity
of Its Environment and the Citation Impact." Environment and Planning B-Planning &
Design 34, no. 5 (Sep 2007): 826-38.
———. "Evaluation of Research and Evolution of Science Indicators." Current Science 89, no. 9
(Nov 2005): 1510-17.
———. "Is Society a Self-Organizing System." Journal of Social and Evolutionary Systems 16,
no. 3 (1993): 331-49.
———. "Mapping Interdisciplinarity at the Interfaces between the Science Citation Index and
the Social Science Citation Index." Scientometrics 71, no. 3 (Jun 2007): 391-405.
———. "'Meaning' as a Sociological Concept: A Review of the Modeling, Mapping and
Simulation of the Communication of Knowledge and Meaning." Social Science
Information Sur Les Sciences Sociales 50, no. 3-4 (Sep-Dec 2011): 391-413.
———. "The Relations between Qualitative Theory and Scientometric Methods in Science and
Technology Studies - Introduction to the Topical Issue." Scientometrics 15, no. 5-6 (May
1989): 333-47.
———. "Scientometrics - French - Callon,M, Courtial,Jp, Penan,H." Scientometrics 30, no. 2-3
(Jun-Aug 1994): 539-41.
77
———. "Theories of Citation?". Scientometrics 43, no. 1 (Sep 1998): 5-25.
Leydesdorff, L., and M. Meyer. "The Scientometrics of a Triple Helix of University-Industry-
Government Relations - (Introduction to the Topical Issue)." Scientometrics 70, no. 2
(Feb 2007): 207-22.
Leydesdorff, L., and I. Rafols. "A Global Map of Science Based on the Isi Subject Categories."
Journal of the American Society for Information Science and Technology 60, no. 2 (Feb
2009): 348-62.
Leydesdorff, L., and J. C. Shin. "How to Evaluate Universities in Terms of Their Relative
Citation Impacts: Fractional Counting of Citations and the Normalization of Differences
among Disciplines." Journal of the American Society for Information Science and
Technology 62, no. 6 (Jun 2011): 1146-55.
Leydesdorff, L., and P. Van den Besselaar. "Scientometrics and Communication Theory:
Towards Theoretically Informed Indicators." Scientometrics 38, no. 1 (Jan 1997): 155-74.
Leydesdorff, L., and C. S. Wagner. "International Collaboration in Science and the Formation of
a Core Group." Journal of Informetrics 2, no. 4 (Oct 2008): 317-25.
Leydesdorff, L., and P. Wouters. "Between Texts and Contexts: Advances in Theories of
Citation? (a Rejoinder)." Scientometrics 44, no. 2 (Feb 1999): 169-82.
Lynch, Michael. Art and Artifact in Laboratory Science: A Study of Shop Work and Shop Talk in
a Research Laboratory. London: Routledge and Kegan, 1985.
———. Scientific Practice and Ordinary Action: Ethnomethodology and Social Studies of
Science. New York: Cambridge University Press, 1985.
Lyon, W. S. "Scientometrics with Some Emphasis on Communication at Scientific Meetings and
through the Invisible College." Abstracts of Papers of the American Chemical Society
189, no. APR- (1985): 4-CINF.
———. "Scientometrics with Some Emphasis on Communication at Scientific Meetings and
through the Invisible College." Journal of Chemical Information and Computer Sciences
78
26, no. 2 (May 1986): 47-52.
———. "Social-Studies of Science and Us .1." Journal of Radioanalytical and Nuclear
Chemistry 85, no. 3 (1984): 131-35.
———. "Social-Studies of Science and Us .2." Journal of Radioanalytical and Nuclear
Chemistry 85, no. 5 (1984): 261-65.
Manis, J. G. "Sociology of Knowledge and Community Mental Health Research." Social
Problems 15, no. 4 (1968): 488-501.
Marcus, G. E. "Ethnography in/of the World-System - the Emergence of Multi-Sited
Ethnography." Annual Review of Anthropology 24 (1995): 95-117.
Mayr, Ernst. " Darwin’s Principle of Divergence." Journal of the History of Biology 25, no. 3
(1992): 343-59.
———. Toward a New Philosophy of Biology: Observations of an Evolutionist. Cambridge:
Belknap Press/Harvard University Press, 1988.
Mayr, Ernst, and W.J. Bock. "Classification and Other Ordering Systems." Journal of Zoological
Systematics and Evolutionary Research 40, no. 4 (2002): 169-94.
McCain, Katherine W. "Longitudinal Author Cocitation Mapping: The Changing Structure of
Macroeconomics." Journal of the American Society for Information Science 35 (1984):
351-59.
McCain, Katherine W. "Mapping Authors in Intellectual Space: A Technical Overview." Journal
of the American Society for Information Science 41 (1990): 433-43.
———. "The Paper Trails of Scholarship: Mapping the Literature of Genetics." Library
Quarterly 56 (1986): 258-71.
McKinley, R. "Why Do Crow and Omaha Kinship Terminologies Exist - Sociology of
Knowledge Interpretation." Man 6, no. 3 (1971): 408-26.
Merton, R. K. . "On the Garfield Input to the Sociology of Science: A Retrospective Collage." In
79
The Web of Knowledge: A Festschrift in Honor of Eugene Garfield, edited by B. Cronin
and H.B. Atkins, 435-48. Medford: Information Today, 2000.
———. "Insiders and Outsiders - Chapter in Sociology of Knowledge." American Journal of
Sociology 78, no. 1 (1972): 9-&.
———. "The Normative Structure of Science." In The Sociology of Science: Theoretical and
Empirical Investigations, edited by N. W. Storer. Chicago: University of Chicago Press,
1942.
———. "The Sociology of Knowledge." Isis 27 (1937): 493–503.
Merton, R. K. , and N.W. Storer, eds. The Sociology of Science: Theoretical and Empirical
Investigations. Chicago: University of Chicago Press, 1973.
Meyer, M. "What Is Special About Patent Citations? Differences between Scientific and Patent
Citations." Scientometrics 49, no. 1 (Sep 2000): 93-123.
Meyer, M., T. S. Pereira, O. Persson, and O. Granstrand. "The Scientornetric World of Keith
Pavitt - a Tribute to His Contributions to Research Policy and Patent Analysis." Research
Policy 33, no. 9 (Nov 2004): 1405-17.
Meyer, M., M. A. Zaggl, and K. M. Carley. "Measuring Cmot's Intellectual Structure and Its
Development." Computational and Mathematical Organization Theory 17, no. 1 (Mar
2011): 1-34.
Moody, J. "The Structure of a Social Science Collaboration Network: Disciplinary Cohesion
from 1963 to 1999." American Sociological Review 69, no. 2 (Apr 2004): 213-38.
Moravcsik, M. J. "Applied Scientometrics - an Assessment Methodology for Developing-
Countries." Scientometrics 7, no. 3-6 (1985): 165-76.
Mulkay, M. "Action and Belief or Scientific Discourse - a Possible Way of Ending Intellectual
Vassalage in Social-Studies of Science." Philosophy of the Social Sciences 11, no. 2
(1981): 163-71.
80
———. "Knowing and Using - Implications for the Sociology of Knowledge." Kolner Zeitschrift
Fur Soziologie Und Sozialpsychologie (1980): 52-72.
———. "Knowledge and Utility - Implications for the Sociology of Knowledge." Social Studies
of Science 9, no. 1 (1979): 63-80.
———. "The Sociology of Science in East and West .1. Sociology of Science in the West."
Current Sociology-Sociologie Contemporaine 28, no. 3 (1980): 1-&.
———. "Methodology in Sociology of Science - Reflections on Study of Radio Astronomy."
Social Science Information Sur Les Sciences Sociales 13, no. 2 (1974): 107-19.
Murdoch, J. "Inhuman/Nonhuman/Human: Actor-Network Theory and the Prospects for a
Nondualistic and Symmetrical Perspective on Nature and Society." Environment and
Planning D-Society & Space 15, no. 6 (Dec 1997): 731-56.
Nakhaie, M. R. "Universalism, Ascription and Academic Rank: Canadian Professors, 1987-
2000." The Canadian Review of Sociology and Anthropology 44 (2007): 361-86.
Nettleton, S., and R. Burrows. "E-Scaped Medicine? Information, Reflexivity and Health."
Critical Social Policy 23, no. 2 (May 2003): 165-85.
Nowotny, Helga. "Human Understanding by Stephen Toulmin." Theory and Society 1, no. 3
(1974): 382-85.
Popper, Karl. Conjectures and Refutations : The Growth of Scientific Knowledge. London:
Routledge, 1959.
———. Objective Knowledge: An Evolutionary Approach. Oxford: Oxford University Press,
1972.
———. The Logic of Scientific Discovery. New York Basic Books, 1959.
Price, Derek J. de Solla. Little Science, Big Science. New York: Columbia University Press,
1963.
Quine, W. "Two Dogmas of Empiricism." The Philosophical Review 60 (1951): 20-43.
81
———. Word and Object. Cambridge: MIT Press, 1960.
Restivo, S. "Commentary - Some Perspectives in Contemporary Sociology of Science." Science
Technology & Human Values, no. 35 (1981): 22-30.
———. "Mathematics and the Limits of the Sociology of Knowledge." Social Science
Information Sur Les Sciences Sociales 20, no. 4-5 (1981): 679-701.
———. "Mathematics and the Sociology of Knowledge." Knowledge-Creation Diffusion
Utilization 4, no. 1 (1982): 127-44.
———. "Science and Technology Studies-Toronto 80, the Joint Annual-Meetings of the
History-of-Science-Society, Philosophy-of-Science-Association, Society-for-the-History-
of-Technology, and Society-for-the-Social-Studies-of-Science, Held in Toronto, Canada,
16-19 October 1980." Science Technology & Human Values, no. 34 (1981): 20-24.
———. "Science and the Sociology of Knowledge - Mulkay,M." American Journal of Sociology
88, no. 1 (1982): 207-08.
———. "Social-Studies of Science - Barber,B." Contemporary Sociology-a Journal of Reviews
20, no. 1 (Jan 1991): 108-09.
Restivo, S., and J. Loughlin. "Critical-Sociology of Science and Scientific Validity." Knowledge-
Creation Diffusion Utilization 8, no. 3 (Mar 1987): 486-508.
Restivo, S. , and J. Croissant. "Social Constructionism in Science and Technology Studies." In In
Handbook of Constructionist Research, edited by J. A. Holstein and J. F. Gubrium, 213-
30. New York: The Guilford Press, 2008.
Richards, E., and J. Schuster. "The Feminine Method as Myth and Accounting Resource - a
Challenge to Gender Studies and Social-Studies of Science." Social Studies of Science
19, no. 4 (Nov 1989): 697-720.
Rollhansen, N. "The Controversy between Biometricians and Mendelians - a Test Case for the
Sociology of Scientific Knowledge." Social Science Information Sur Les Sciences
Sociales 19, no. 3 (1980): 501-17.
82
Rossiter, M. W. "The Matthew-Matilda Effect in Science." Social Studies of Science 23, no. 2
(May 1993): 325-41.
Roth, W. M. "Situated Cognition and Assessment of Competence in Science." Evaluation and
Program Planning 21, no. 2 (May 1998): 155-69.
Roth, W. M., and K. B. Lucas. "From ''Truth'' to ''Invented Reality'': A Discourse Analysis of
High School Physics Students' Talk About Scientific Knowledge." Journal of Research
in Science Teaching 34, no. 2 (Feb 1997): 145-79.
Roth, W. M., and M. K. McGinn. "Inscriptions: Toward a Theory of Representing as Social
Practice." Review of Educational Research 68, no. 1 (Spr 1998): 35-59.
———. "Knowing, Researching, and Reporting Science Education: Lessons from Science and
Technology Studies." Journal of Research in Science Teaching 35, no. 2 (Feb 1998):
213-35.
Roth, W. M., M. K. McGinn, and G. M. Bowen. "Applications of Science and Technology
Studies: Effecting Change in Science Education." Science Technology & Human Values
21, no. 4 (Fal 1996): 454-84.
Salamini, L. "Gramsci and Marxist Sociology of Knowledge - Analysis of Hegemony - Ideology
- Knowledge." Sociological Quarterly 15, no. 3 (1974): 359-80.
Shapin, S. "Here and Everywhere - Sociology of Scientific Knowledge." Annual Review of
Sociology 21 (1995): 289-321.
Shwed, Uri , and Peter S. Bearman. "The Temporal Structure of Scientific Consensus
Formation." American Sociological Review 75 (2010): 817-40.
Siler, K. S. , and N. McLaughlin. "The Canada Research Chairs Program and Social Science
Reward Structures." The Canadian Review of Sociology 45 (2008): 93-119.
Sismondo, Sergio. "Science and Technology Studies and an Engaged Program." In The
Handbook of Science and Technology Studies of Science and Technology Studies, edited
by E.J. Hackett, Amsterdamska, O., Lynch, M. And Wajcman, J. . 13-31: The MIT Press,
83
2008.
Slocum, R. "Polar Bears and Energy-Efficient Lightbulbs: Strategies to Bring Climate Change
Home." Environment and Planning D-Society & Space 22, no. 3 (Jun 2004): 413-38.
Smith, J. W. "Primitive Classification and the Sociology of Knowledge - a Response to Bloor."
Studies in History and Philosophy of Science 15, no. 3 (1984): 237-43.
Sokal, R.R., and P. Sneath. Principles of Numerical Taxonomy. San Francisco: W.H. Freeman,
1963.
Straus, M. A. "Bucking the Tide in Family Violence Research." Trauma Violence & Abuse 9, no.
4 (Oct 2008): 191-213.
———. The Controversy over Domestic Violence by Women - a Methodological, Theoretical,
and Sociology of Science Analysis. Violence in Intimate Relationships. edited by X. B.
Arriaga and S. Oskamp1999.
Sullivan, T. A. "Sociology of Science in Europe - Merton,Rk, Gaston,J." American Journal of
Sociology 85, no. 3 (1979): 678-80.
Toulmin, Stephen E. . "The Evolutionary Development of Natural Science." American Scientist
55, no. 4 (1967): 456-71.
———. Human Understanding: The Collective Use and Evolution of Concepts. Princeton:
Princeton University Press, 1972.
Tibbetts, P. "The Sociology of Scientific Knowledge - the Constructivist Thesis and Relativism."
Philosophy of the Social Sciences 16, no. 1 (Mar 1986): 39-57.
Twain, M. . "Report of My Death." http://twainquotes.com/Death.html.
Uebel, T. E. "Logical Empiricism and the Sociology of Knowledge: The Case of Neurath and
Frank." Philosophy of Science 67, no. 3 (Sep 2000): S138-S50.
Vinkler, P. "An Attempt for Defining Some Basic Categories of Scientometrics and Classifying
the Indicators of Evaluative Scientometrics." Scientometrics 50, no. 3 (Mar-Apr 2001):
84
539-44.
———. "Characterization of the Impact of Sets of Scientific Papers: The Garfield (Impact)
Factor." Journal of the American Society for Information Science and Technology 55, no.
5 (Mar 2004): 431-35.
———. "Eminence of Scientists in the Light of the H-Index and Other Scientometric
Indicators." Journal of Information Science 33, no. 4 (2007): 481-91.
———. "Evaluation of the Publication Activity of Research Teams by Means of Scientometric
Indicators." Current Science 79, no. 5 (Sep 2000): 602-12.
———. "Indicators Are the Essence of Scientometrics and Bibliometrics." Scientometrics 85,
no. 3 (Dec 2010): 861-66.
———. "Scientometrics and Scientometricians in 2011." Journal of the American Society for
Information Science and Technology 62, no. 7 (Jul 2011): 1430-32.
———. "Some Practical Aspects of the Standardization of Scientometric Indicators."
Scientometrics 35, no. 2 (Feb 1996): 237-45.
———. "Words and Indicators - as Scientometrics Stands." Scientometrics 30, no. 2-3 (Jun-Aug
1994): 495-504.
Walsh, Denis. "Evolutionary Essentialism." British Journal of the Philosophy of Science 57
(2006): 425-48.
Walton, J. "Discipline, Method, and Community Power - Note on Sociology of Knowledge."
American Sociological Review 31, no. 5 (1966): 684-89.
Weiss, R. M., and L. E. Miller. "The Concept of Ideology in Organizational Analysis - the
Sociology of Knowledge or the Social-Psychology of Beliefs." Academy of Management
Review 12, no. 1 (Jan 1987): 104-16.
Whatmore, S. "Materialist Returns: Practising Cultural Geography in and for a More-Than-
Human World." Cultural Geographies 13, no. 4 (Oct 2006): 600-09.
85
Whatmore, S., and L. Thorne. "Elephants on the Move: Spatial Formations of Wildlife
Exchange." Environment and Planning D-Society & Space 18, no. 2 (Apr 2000): 185-
203.
Whatmore, S. J. "Mapping Knowledge Controversies: Science, Democracy and the
Redistribution of Expertise." Progress in Human Geography 33, no. 5 (Oct 2009): 587-
98.
White, H. D. "Author Co-Citation Analysis: Overview and Defense." In Scholarly
Communication and Bibliometrics, edited by C.L. Borgman. 84-106. Newbury Park:
Sage, 1990.
———. "Introduction." Journal of the American Society for Information Science 41 (1990): 430-
31.
White, H. D. & Griffith, B.C. "Author Cocitation: A Literature Measure of Intellectual
Structure." Journal of the American Society for Information Science 32 (1981): 163-71.
Winner, L. "Conflicting Interests in Science and Technology Studies - Some Personal
Reflections." Technology in Society 11, no. 4 (1989): 433-38.
———. "On the Foundations of Science and Technology Studies." Bulletin of Science
Technology & Society 6, no. 2-3 (1986): 219-21.
Woolgar, S. "The Turn to Technology in Social-Studies of Science." Science Technology &
Human Values 13, no. 1-2 (Win-Spr 1988): 203-04.
———. "The Turn to Technology in Social-Studies of Science." Science Technology & Human
Values 16, no. 1 (Win 1991): 20-50.
———. "The Very Idea of Social Epistemology + Fuller,Steve - What Prospects for a Truly
Radical Radically Naturalized Epistemology." Inquiry-an Interdisciplinary Journal of
Philosophy 34, no. 3 (Sep 1991): 377-89.
———. "What Is the Analysis of Scientific Rhetoric for - a Comment on the Possible
Convergence between Rhetorical Analysis and Social-Studies of Science." Science
86
Technology & Human Values 14, no. 1 (Win 1989): 47-49.
Wray, Brad K. Kuhn’s Evolutionary Social Epistemology. Cambridge: Cambridge University
Press, 2011.
Yablonsky, A. I. "Stable Non-Gaussian Distributions in Scientometrics." Scientometrics 7, no. 3-
6 (1985): 459-70.
Yearley, Steven. Making Sense of Science: Understanding the Social Studies of Science. Sage
Publications Ltd, 2005.
Young, M. F. D. "Taking Sides against Probable Problems of Relativism and Commitment in
Teaching and Sociology of Knowledge." Educational Review 25, no. 3 (1973): 210-22.
Ziman, John. Real Science: What It Is and What It Means. Cambridge: Cambridge University
Press, 2000.