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PADEV

PADEV. PARTICIPATORY ASSESSMENT OF DEVELOPMENT a new methodology for impact assessment. PADEV. Case Presentation for the conference Evaluation Revisited By Fred Zaal and Wouter Rijneveld Utrecht, May 20, 2010. Contents. Background of the case Description of the case Methodology

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PADEV

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  1. PADEV PARTICIPATORY ASSESSMENT OF DEVELOPMENT a new methodology for impact assessment

  2. PADEV Case Presentation for the conference Evaluation Revisited By Fred Zaal and Wouter Rijneveld Utrecht, May 20, 2010

  3. Contents • Background of the case • Description of the case • Methodology • Illustrative findings • Values, Quality, Complexity • Improvements foreseen

  4. Background of the case Perceiving shortcomings of ‘impact evaluations’ • Not really about impact (rather outcome – output) , too short term • Lack of attention for context • External factors • Other interventions • Focus on predetermined (by whom?) results • If participative, then ‘dependency bias’

  5. Background of the case Longing for • True participation and ownership • True holism, but not vagueness • Getting rid of the ‘dependency bias’ And seeing preliminary work of Ton Dietz in Kenya…

  6. Description of the case ICCO, Prisma and Woord en Daad (Dutch, 2 NGO’s 1 network) joined hands with • University of Amsterdam (NL) • University of Development Studies (Ghana) • Expertise pour le Développement au Sahel (Burkina Faso)

  7. Usualperspective backdonor INGO • Activities • Results • Outputs • Outcomes • Impact • PM&E NGO Project a in community x

  8. Other backdonors Other INGO’s NGO 2 NGO 3 • Government • Local • State • National Project c Project c Project b Project b Project a Project a Companies (e.g. telecom) Natural Physical Economic Human Social Political Cultural Private initiatives backdonor INGO NGO 1 Project c Project b Project a Community x Community x Very poor – poor – average – rich – very rich Local influences National influences Global influences

  9. Methodology Projects Actors History History Community x Very poor – poor – average – rich – very rich History Changes in context

  10. 3 day workshops • 60 people from area of 20,000 • Subgroups: men, women, old, young(officials and project staff separate group) • Individual life history questionnaire data about participants, parents, siblings, children (total 600 persons per workshop) • 4 rounds of 3 workshops each(3 x 3 workshops concluded)

  11. Contents of workshop Toolbox of exercises: • Context: shocks, trends (6 capitals), wealth classes • Interventions: inventory (by actor, sector, years) + valuation • 5 best / worst interventions: in depth exercises: • Shift in perception over time • Effects on wealth classes and capitals • Relation between trends and interventions (cause, mitigation)

  12. Illustrativefindings • Incredibly detailed historical profile + descriptions of wealth categories

  13. Numbers of Projects

  14. Best / Worst projects

  15. Impact on wealth classes

  16. Impact on wealth classes

  17. Values and Principles • Principles: • Evaluation = “valuing” something (diversified) values of the people • Evaluation (esp. at impact level) must be done in context, relative to other factors and actors. • Values: • Emerge from participants

  18. Quality Standards • Validity (do you measure what you want to measure?) • Impact = long term • Inter-subjectivity (negotiated consensus) instead of assumed objectivity • Reliability / replicability(are findings stable?) • Convergence of type of results after 9 workshops • Additional trials at different scale / different target groups (some still in process) • Meticulous reporting, External Reference Group, AMAP Feed back

  19. Complexity… … is the essence of this method Multiple relations between shocks, trends (per capital, function of time), interventions (per type of actor / sector, function of time) and effects on people in wealth classes, capitals (function of time)  Insight in some of these relations

  20. Complexity

  21. Improvements / trade-offs • Triangulation • With external data (e.g. on trends) • With the Partner agency’s knowledge and monitoring system • Selection of participants • ‘opinion leaders’ (officials are separated) • Trade off between ‘randomization’ and needs for analyses of the groups

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