Collective Action Dilemma after China’s Forest Tenure Reform: Operationalizing Forest Devolution in a Rapidly Changing Society
Why this work is in the frame
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Bibliographic record
Abstract
Devolution is a promising tool to enhance forest management. The literature has discussed many factors that affect the outcomes of forest devolution policies; however, insufficient attention has been paid to the role of exogenous socio-economic changes. Using the longitudinal case study method, we focus on how socio-economic changes affect the effectiveness of forest devolution policies using a case from Southeast China. We find that in this case, although forest devolution succeeded in granting farmers sufficient forest rights, it failed to incentivize farmers to contribute to managing forests because of the dramatic changes in socio-economic contexts. Economic development and outmigration reduced farmers’ dependence on forest income, elevated the costs of silvicultural operations, and posed market risks, thereby reducing farmers’ enthusiasm about managing forests; outmigration also weakened community leadership and impeded the collective action of making forest investments. Eventually, socio-economic changes compromised the positive stimulus caused by forest devolution and contributed to the collective action dilemma of managing forests after the reform. We argue that operationalizing forest devolution in developing countries needs to consider the exogenous socio-economic changes that may enhance or counteract the effects of devolution policies, and that more autonomy should be granted to communities to make policies adaptative to their local socio-economic dynamics.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it