Unfulfilled promises, illegal resource extraction, and the legitimacy of park management in Ethiopia
Bibliographic record
Abstract
Protected area management in developing countries faces legitimacy issues, especially with supposed participatory governance reforms and social-ecological disturbances. The legitimacy of decentralized governance, however, depends on its response to conservation promises and illegal resource extraction. This paper examines how unfulfilled promises, illegal resource extraction, and the legitimacy of protected area governance interact in agro-pastoralist communities. In this study we draw on primary data collected through household surveys, group discussions, and interviews. Using thematic analysis, we find that failure to deliver on promises of livelihood projects erodes governance legitimacy by fostering mistrust and injustice. This increases communities’ vulnerability to climate shocks and drives illegal resource extraction, which in turn weakens regulations and fuels further illegal activity through informal networks. Ultimately, pro-conservation behavior hinges on keeping promises and legitimate governance, not past motivations. We highlight the need to fulfill promises of livelihood projects as a pathway to restore the legitimacy of protected area governance and address livelihood vulnerability.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".