CHALLENGES TO PARTICIPATORY DEVELOPMENT IN A RURAL CROSS-BORDER AREA OF THE WESTERN BALKANS
Bibliographic record
Abstract
The World Bank, the Canadian International Development Agency (CIDA), USAID and the International Relief/Development Project (IRDP) concluded in different reports that participatory development programs are invariably more effective at addressing local needs and interventions are more often sustained given the engagement of local actors. The main objective of this paper is to present a detailed appraisal of the implementation process of a well-known participatory approach (the UNDP-designed Area-Based Development - ABD) in the challenging context of a rural, cross-border area (in the Western Balkans). Besides reviewing the theoretical and empirical advantages of participatory and endogenous development, this case study reflects the practical shortcomings related to the selection process of a target area and to obtaining commitment from different agents in a post-conflict zone. This article also highlights that adequate implementation of participatory practices is crucial to obtain accurate quantitative and qualitative data (to guide the development agenda) and secure the involvement of both local and (inter)national actors. The latter is an important factor in fostering long-term engagement to development strategies and the achievement of results that are relevant for the local community and in harmony with national policies and international agreements.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.038 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.015 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".