Public Policies, Laws, Sociocultural Norms, and the Status of Women’s Empowerment in Agriculture and Livestock in Senegal: Protocol for a Scoping Review
Bibliographic record
Abstract
It is a descriptive scoping review protocol, which aim is to provide an overview of the dynamics of access and control that women involved in agriculture and livestock have over resources in the Senegalese contexts. The concept of resources encompasses all means, services, and opportunities that enable the socioeconomic empowerment of women (work, information, education, training, material goods, land, savings, livestock, etc.). This study is part of a larger action-research project entitled Elles Luttent contre les Zoonoses (ELUZO), launched in 2023 for a duration of five years, led by the University of Montreal and the University of Guelph, and funded by Global Affairs Canada (GAC). The project was designed and implemented in collaboration with Senegalese organizations, including Cheikh Anta Diop University, the NGO COMI, and the association Adaf Youngar. ELUZO aims to strengthen the power of women and girls in combating zoonoses in Senegal and Burkina Faso, adopting an integrated, intersectoral One Health approach. The present scoping review was initiated and funded as part of a pre-intervention assessment launched in 2024, aiming to identify policies, laws, and interventions related to the empowerment of women livestock farmers in the target countries. It will also constitute the first objective of a doctoral research project examining gaps between policies, legal frameworks, sociocultural norms, and the actual level of autonomy of Senegalese women.
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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 | 0.138 | 0.116 |
| Meta-epidemiology (narrow) | 0.003 | 0.005 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.054 | 0.008 |
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".