MODELLING PUBLIC KNOWLEDGE AND

ATTITUDE TOWARDS GENETICALLY MODIFIED MAIZE

Introduction

Statement of the problem

Objectives

Methodology

Conclusion

Potential benefits of genetically modified food to developing

countries.

The variable nature of a community's attitude on issues of

science and technology.

Information dissemination and effect of its failure.

Public sensitization about the importance of using biotechnology

to improve food production.

The study sought to establish the associations between knowledge

as an independent variable and attitude as a dependent variable

using generalized linear model despite controlling for a range of

other important characteristics such as age, education and social class.

This research assess different ways on how knowledge and

attitude relate to adoption of genetically modified maize and apply

the logistic Model to explain the relationship between variables

from the data.

We expect to know the significance of knowledge on attitude

towards adoption of Genetically modified organisms.

Potential benefits of GM organisms to developing

countries.

The relationship between Consumer attitudes and general

socio-political attitudes on genetically modified foods.

Importance of knowledge and attitude in determining the

development of biotechnology on agricultural

commodities.

The contribution of information dissemination to Public

knowledge and attitude towards genetically modified

organisms.

The use of the deficit model to explain public negative attitude

towards biotechnology referring to public’s scientific

ignorance.

Reviewed properties of the past fitted models to determine the

goodness of the model.

Contingent valuation (cv) approach on acceptance of GM food

by the public.

Does knowlegde on biotechnology influence its adoption?

Does knowledge influence attitude of biotechnology?

Does both knowledge and attitude influence adoption of Gm

maize in the four counties?

General objective.

To model public knowledge and attitude towards genetically

modified maize and apply in Uasin-ngishu, Transzoia and Elgeyo

marakwet counties.

Specific Objectives

• To propose a model for public knowledge and attitude towards

genetically modified maize.

• To empirically study the properties of the proposed model.

• To apply the model on data collected in Uasin-ngishu,

Transzoia, and Elgeyo marakwet counties.

This study helps the public who are lacking a proper understanding of

the relevant facts, people who fall back on mystical beliefs and

irrational fears of the unknown. If one accepts this hypothesis, the

obvious implication for biotechnology policy is that public

information campaigns should be instigated to remedy the public’s

disenchantment with biotechnology.

The study will also benefit scholars who are utilizing survey

methods that consistently uncover the associations between

knowledge of and attitude towards science despite controlling

for a range of other important characteristics such as age,

education and social class and often should not choose to

ignore this finding that culture, economic factors, social and

political values and worldviews. This are all important in

determining the public’s attitude towards science and hence

broaden the scope of the study to justify the need of GM foods

to increase food security in the country.

This study used primary data which was collected from

farmers of Uasin-ngishu, Transzoia and Elgeyo-marakwet

counties in Kenya.

The data was acquired through a survey where a person was

required to fill a questionnaire and was given a small briefing

about GM maize and products before the questionnaire was

administered.

It contains knowledge and attitude variables towards GM

maize where attitude was represented by two variables willing

to adopt and willing to buy.

Public attitude on GM maize represented by willingness to

buy and willingness to adopt as dependent variables and

knowledge as independent variable was computed.

The model used gives the level of adoption of GM maize in relation to public knowledge.

The kind of data that were used in this study was dichotomous

and the most preferable model applied in this case was logistic

model because the outcome side of the regression equation

was constrained to be in the interval (0, 1).

In the model that is going to be applied,

Pi is assumed to be the probability of consumers accepting

GM maize.

Xij is the matrix of independent variables , where i denotes the

ith respondent, and j denotes the jth independent variable,

which is consisted of consumers’ personal characteristics such

as gender and age, his/her socio-economic variables.

Pi = F (Zi) = F (BXi') = 1/ [1+exp (-Zi)] …………….. (1)

where, F (Zi) is used to denote the value of logistic cumulative

density function (CDF) associated with each possible value of the

underlying index Zi, which equals to an unobserved index level for

the ith observation, and which can be formalized as equation (1)

because βXi' is a linear combination of the independent variables in

equation (1); β = (β0, β1.....βj) is a vector of parameters we will

estimate.

Willingness_adopt = 0

Knowledge_GM

Willingness_buy 0 1

0 30 17

1 13 15

Willingness_adopt = 1

Knowledge_GM

Willingness_buy 0 1

0 11 19

1 10 21

prop.table (table1)

Willingness_adopt = 0

Knowledge_GM

Willingness_buy 0 1

0 0.22058824 0.12500000

1 0.09558824 0.11029412

Willingness_adopt = 1

Knowledge_GM

Willingness_buy 0 1

0 0.08088235 0.13970588

1 0.07352941 0.15441176

After getting the summary of glm, it was clear that the

intercept and standard error of the intercept was 0.38425 while

that of the first variable was 0.1136 and for the second was

0.2137 respectively. The residual standard error is 0.4882. The

multiple R-squared was 0.6459 while adjusted R-squared was

0.5052 with a p-value of 0.01179. Looking at the model they

concluded that it was significant because the R-squared is

more than 0.5. Checking if the variables are significant, we

look at the Pr (>|z|) which is 5.936 2.4e-08 which is very

significant.

Hence the model is 1/exp(-0.3843+0.1136X1+0.2137X2)

Willingness_buy Knowledge_GM Willingness_adopt

0.0

0.2

0.4

0.6

0.8

1.0

The success of a GM crop program would depend on the

acceptability of its products by citizens, it was therefore

suggested not only that scientists now had a duty to go out and

communicate the benefits of science to a wider public, but also

that a more ‘scientifically literate’ public would be more

supportive of scientific research programs and more

enthusiastic about technological innovations. The results of

this survey shows that more than two-third of the farmers in

the counties surveyed were aware of GM crops, so it is

generally possible to engage them in the debate. However,

knowledge, sources of information, and attitudes varied by

level of education, gender and socioeconomic grouping.

However, there is significance between the independent and

the dependent variable according to the data analysis results.

Studies tracking public opinion should be conducted regularly,

in order to determine knowledge levels, capture the impact of

knowledge activities, and reveal trends. Studies should be

extended to the 47 counties in order to include these segments

of the population in the national discourse. The present study

provided some important insights to improve the methodology.

First, the different counties represent different types of

consumers. However, the number and respective percentage of

people that do farming activity in each county is not known.

Household surveys could solve this problem, and they are

therefore highly recommended. Further, future surveys can

move from open-ended to closed-ended questions.

i. CHERN et al (2003): Consumer acceptance and willingness to pay for GM

foods.

ii. DEGROOTE, H (2002):Maize yield losses from stem borers in Kenya.

iii. DE GROOTE H., D. BERGVINSON, and B. ODHIAMBO

(2004):Debunking the myths of GM crops for Africa.

iv. S. MUGO et al (2003): Assessing the potential impact of Bt maize in Kenya.

v. FAO. (2004). FAO (Food and Agriculture organization), 2004. The state of

food and agriculture 2003-2004.

vi. PINSTRUP-ANDERSEN, P. and SCHIOLER, E (2000): Seeds of

Contention:

vii. SPRINGER, A. et al (2002):Comparing Consumer Attitudes Towards

Genetically Modified Food in Europe. Mimeo.

viii. VERDURME, A. and VIAENE, J. (2002): Consumer Beliefs and Attitudes

Towards Genetically Modified Food:

ix. Kimenju et al (2004) : consumer awareness and attitude towards genetically

modified food.

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