Grassroots Participation for Infrastructural Provisioning in Northwest Cameroon: Are Village Development Associations the Panacea?
Bibliographic record
Abstract
Local communities are the loci of spatial development initiatives as they wrestle with the problem of resource scarcity and to fill the void left by the reduction in state services. This paper explores the gender dimension of grassroots participation in community development in selected localities of the Northwest Province of Cameroon. It outlines the gender roles and biases of grassroots participation through Village Development Associations (VDAs), which have become the prevalent vehicles for the galvanization of indigenous resource and building of social and human capital for project execution. Projects successfully executed include the construction of bridges and community halls, renovation of school buildings and health centres, digging and maintenance of earth roads, and the provision of pipe-borne water. In spite of communitarian efforts, VDAs are finding it difficult to embark on large-scale infrastructural development projects such as rural electrification, road construction, water supply and health centres, all of which require huge capital investments and a high degree of technical expertise. Participation is also affected by a litany of gender-based inequalities, mismanagement, ambiguous and vested interests of the elite, and complex operational structures of VDAs coupled with a politicized institutional environment. The paper concludes that although VDAs are not the cure-all, if revitalized, they can determine the local development agenda and become conduits for direct efforts at poverty reduction.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".