Spatializing knowledge in urban governance

Isa Baud and N. Sridharan University of Amsterdam

School of Planning and Architecture, Delhi

Knowledge in urban governance?

• Urban governance requires networking for steering development processes

• Knowledge required to support processes: providing legitimacy, relevance, accountability

• Spatializing knowledge links variety of knowledge sources to one locality – integrated understanding

Focus on potential of tools for more participatory urban governance

Urban governance networks

• From hierarchy to network? • Theoretically, but complexity in practice • Re-scaling – Brenner

• Urban regimes: with whom does the government work? • Growth coalition of government and private sector • Government and citizen networks for QoL issues• Intra-government hierarchy for economic growth and

infrastructure investment

Governance models

.

Network governance

Marketgovernance

Hierarchicalgovernance

Basic principle Reciprocity CommercialExchange

Political andAdministrativePower

Coordination principle

Collaboration Price Rules

Roles ofgovernment

Govt. as partner Govt. as enabler,setting standardsand contractingout

Central ruler(differentlevels)

Key values Collaborative decisions on distribution issues

consumer choice Public goods

Types of knowledge and exchange Tacit Contextual-

embedded knowledge;

technical, economic

Contextual-embedded knowledge;

community-based

Contextual –embedded knowledge:

political and network levels

Codified knowledge (analytical, regulatory, standards)

Main actors

Individual experience

Professional knowledge among sector professionals

Community knowledge spread through social networks

Political knowledge within socio-political networks

Academically, professionally taught and diffused

Knowledge in urban governance

• Who are producers and users? • What knowledge instruments are used in

these networks? Incentives?• Whose knowledge is included, excluded?• What knowledge coalitions are formed?

– Urban government and private developers – Civic organisation and citizens – Government and civic organisations

Knowledge in Local government

• Administrative knowledge used:– Planning instruments and procedures; – Funding programme requirements

• Knowledge excluded: – Local community knowledge, – Academic knowledge from other sources;– Own databases for trend analyses; – Remote sensing sources;

• Potential exists for spatial information (Tool 1)

Community perspectives on knowledge

• Knowledge used by communities: • Experience of lived spaces (quality of life issues) • Local knowledge on opportunities and limitations• Knowledge on social and political relations

• Tacit community knowledge, social and political relations often ignored in urban management

• For inclusion participatory knowledge generation can provide new instruments (Tool 2)

E-governance: interaction and knowledge exchange (Tool 3)

• Assumptions: increase of • Efficiency• Revenues• Accountability• Transparency• Reduce corruptions• Learning

• But– Exclusionary or participatory?

Untapped potential of integrated knowledge (Tool 4)

• Geographical information systems– Matching thematic information to localities– Visualization of spatial patterns and trends– Overlay of different sources of information

=> Knowledge integration and monitoring

Approaches to spatial knowledge production

• Utilizing existing databases – Census, ..(tool 1)• Drawing in tacit knowledge by participatory

methods – community, professional, CSO sources (tool 2)

• Analyzing e-based information (tool 3)• Combining sources of information – remote

sensing, mining databases, web2.0 (tool 4)

Baud, Sridharan and Pfeffer (2008),

Tool 1- Using Census for mapping ‘Hotspots’ of poverty in Delhi, with

Multiple deprivation index

ISA,SRI & KarIn (c) 2007

Tool 1: Mumbai & Chennai Poverty hotspots

ISA,SRI & KarIn (c) 2007

Tool 1: comparing databases for analysis:

Poverty in slums?

Basic and formal built-up area

Informal built-up area

Low density High density

A type B type

Urban structures in Delhi (India)

Baud, I, Kuffer, M, Pfeffer, K, Sliuzas, R V & Karuppannan, S 2010 Understanding heterogeneity in metropolitan India : the added value of remote sensing data for analyzing sub - standard residential areas . International journal of applied earth observation and geoinformation: JAG 12 359-74.

Combining understandings• Tool 1 based on calibrating in-depth knowledge

of local situations: – Households’ priorities in livelihood strategies– Negotiations with organisations providing for needs

(housing, employment, services)– Political processes of provision (middle-class route

versus poor households’ political channels (councilors))

– Heterogeneity in cities: gauthans, lifestyle cities (source: van Dijk, 2008,2009, 2010)

Tool 2: drawing in tacit knowledge – participatory workshops

• Councillors and administrators combined

• Setting issues priorities • Setting spatial priorities• Outcome:

– Common understanding – Contestations

Tool 2: Prioritizing issues by ward in Kalyan -Dombivili

Tool 2: Cumulative priorities and localities Source: Pfeffer, Martinez, Baud, Sridharan, 2010

Tool 3: E-based grievance analysis Source: Martinez, Pfeffer, Van Dijk, 2009

Tool 3. Complaints and Index Multiple deprivation

• Complaints not necessarily concentrated in the most deprived areas according to IMD. (Source: Pfeffer, Martinez, Baud, Sridharan, 2010 )

 

Ward 24

Tool 3: Classifications and embedding Source: Richter, Miscione, De, Pfeffer, 2010

• Databases based on mixed classifications• Criteria and political

• Digitizing local databases still unevenly implemented

• Linkages between local, state and national government still uneven

• Exclusionary potential underestimated

Tool 4: Integrating different knowledge sources

• Example Hubli-Dharwad, SPA Master students, coordinated by N. Sridharan

• Fieldwork combined with Census-based deprivation mapping

• Consultations with local government and communities

• Analysis integrates different types of knowledge: conclusions fed back to local government

“In conclusion” Tools, claimed potentials and unnamed limitations

• 1 – utilizing existing databases strategically – spatialisation provides extra information on urban segregation and ‘hotspots’

• 2 – database classifications may be mixed, providing skewed analytical results

• 3 - tacit knowledge supports more inclusionary processes, provided stakeholders are not excluded

• 4 – e-based grievance systems may be efficient, but danger of excluding needs when deprived groups do not utilize these channels

• 5 – integrated knowledge base provides more balanced picture: needs feedback in policy discussions 25

“In conclusion” Linking tools to urban governance

Network governance

Hierarchical governance

Knowledge governance

Tool 1: analyzing existing databases with theoretical framework

+ ++ ++

Tool 2: tacit knowledge through participatory processes

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Tool 3: mining/creating databases

+ ++ ++

Tool 4: integrating various sources of information and knowledge

++ + ++

Thank you!