The effect of collective forestland tenure reform in China: Does land parcelization reduce forest management intensity?
Why this work is in the frame
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Bibliographic record
Abstract
China implemented a new round of collective forestland tenure reform during 2003–2013. In this reform, forestland owned by villages or township collective organizations were divided into a great number of small plots and allocated to member households of the collectives. A widespread concern about the reform is that parcelization of forestland might limit farmers’ incentives to invest in forest management. This paper examines the factors affecting farmers’ investment in forest management using household data collected in four provinces in 2010. The results show that the intensity of a household's investment in forest management is negatively affected by its nonfarm income and the average size of forest plots, but positively affected by the easiness in obtaining loan and the technical assistance the household receives. We argue that the counterintuitive effect of nonfarm income on investment intensity is due to the increasing marginal cost of own labor input. The effects of forest plot size and easiness in obtaining loan suggest that households have limited amount of capital to invest in forest management. Because of this constraint, parcelization of forestland resulted from the recent reform has not yet caused any reduction of the intensity of investment in forest management.
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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 | 0.001 | 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