A stake in their future: Advancing local community engagement in Northeast Nigerian development initiatives
Bibliographic record
Abstract
This article examines the level of local community engagement in development initiatives in the northeast of Nigeria, highlighting the importance of local community engagement in the successful implementation and sustainability of development projects and their current challenges. The study delves into the existing literature and reports using a desk research methodology, providing a comprehensive overview of current practices and the barriers hindering effective community involvement. This exploration identifies several key research gaps, including the lack of consensus on effective community engagement measurement, insufficient understanding of participation dynamics, and limited investigation into the long-term effectiveness of capacity-building initiatives. In response to these gaps, the article proposes strategies to improve community engagement in the region, such as developing robust metrics for community engagement, implementing inclusive participation practices, and incorporating capacity-building components in development initiatives. The article underscores the critical need for further research in this area and advocates for more inclusive, sustainable, and effective community engagement in Northeast Nigeria’s development efforts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".