Analysis of the interrelationships of stakeholders involved in the management of transhumance in southern Benin
Bibliographic record
Abstract
Abstract The management of pastoral mobility is a stakeholder-centered approach for the integration of resource conservation and agricultural development. This management of space and its resources is the responsibility of a group of actors who are responsible for resolving conflicts of interest. This study aimed at analyzing the influence of transhumance stakeholders in the municipality of Djidja in southern Benin thanks to semi-structured interviews, which were conducted with 300 transhumance actors. The Likert scale (1 to 5) was used to assess the levels of influence and focus groups were conducted. The results obtained showed that several stakeholders were involved in transhumance with diverse interests, backgrounds, knowledge and power (p < 0.05). The majority of farmers (72%) blame transhumant herders whose practices are source of multiple conflicts. The analysis indicated a strong influence with highly significant differences (p < 0.001) in the management of transhumance by four stakeholders including the communal transhumance committee, the association of herders, the Garso (Scout and intermediary for transhumant herders) and the transhumant herder. This research demonstrates how the systematic analysis of the activities carried out by the actors, the interconnected activities between them and their relationships can offer insights for a better coordination of transhumance. For management to become reality, it is important building partnership between the various stakeholders linked by transhumance in southern Benin.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".