The Challenge of Ownership in the Communal Management of Natural Resources by the Local Political Decision Makers and of Gender Mainstreaming: The Case of Protected Areas in Senegal
Bibliographic record
Abstract
"To cope with ecological, socio-economical and demographical changes, the rural populations in Senegal have tried to combat the degradation of their environment by promoting some local adaptation strategies. Indeed, in several areas, the populations have taken the initiative of restricting some inter-village forestry and pastoral land ranges to exploitation, so as to protect, conserve and use them to cater to their various needs. These local management measures are not, in most cases, taken into account by the rural council which is the local institution mandated for the management of the natural resources by virtue of Decree No. 96-1134 as of December 27th 1996. The Decree addresses the implementation of the act of law relative to the transfer of authority to the provinces, communes and rural communities with respect to the management of the environment and of natural resources. Most of the local representatives are more concerned with the other functions rather than those related to natural resource management. Yet, the populations they represent earn their livelihood mainly from the exploitation of the available natural resources. This work examines the difficulties the populations face so as to succeed socially and above all benefit properly from the favorable socio-economic consequences of these protected areas in the absence of any external support. On the basis of a socio-economic, organizational, and institutional evaluation as well as gender-based studies that considered situations with or without any external support, we pay close attention to local mechanisms of support to the populations with communal local initiatives; to empowerment of the local decision-making representatives in charge of the environment; to dialogue between communities and local stakeholders; and to the level of creativity in mobilizing the required financial 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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.034 | 0.037 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".