Analysis of the Institutional Framework for the Management of Community Areas Through the Prism of Institutional Bricolage: The Case of Benin’s Bouche du Roy
Bibliographic record
Abstract
Natural resource governance requires the collaboration of various stakeholders, including community, state and private institutions. Using an institutional bricolage theoretical framework and stakeholder theory, we analyzed stakeholder influences and interrelationships in the management of the Bouche du Roy Community Biodiversity Conservation Area (CBCA). We conducted semi-structured interviews with seventy-three (73) participants from responsible organisations and agencies and the local population and undertook participatory observations and documentary analyses. Our analysis reveals that the management of the CBCA is characterized by two main institutional features. The first consists of arrangements that govern the organization of stakeholders and the establishment of the local management association. The second is a hybridization of conservation strategies that includes cultural and spiritual practices. Our analysis also reveals that considering priorities and characteristics of the local population facilitates the implementation of the CBCA ecosystems’ conservation plan, despite differences between conservation objectives and the population’s needs. The mapping of actor relations reveals unequal influence across stakeholder categories and weak capacity and autonomy of the responsible local association. The management of the CBCA would benefit from reinforcing local actors’ capacity, thus improving the balance of decision-making responsibility and fostering the local management association’s autonomy. This case study sheds light on the dynamics of influence in the multiscale institutional management of community natural resources.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.022 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".