Influence of rural households' livelihood capital on income derived from participation in the Forest Carbon Sequestration Project: a case from the Sichuan and Yunnan Provinces of China
Why this work is in the frame
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Bibliographic record
Abstract
© 2018 BioOne. All rights reserved. We analyze survey data collected from interview of 367 randomly selected rural households from the Sichuan and Yunnan provinces of China to assess the influence of rural households' livelihood capital (physical, financial, human, natural, and social capital) on their income from participation in the forest carbon sequestration project. The project is implemented under the Climate, Community, and Biodiversity standards. Results show that, with regional differences controlled, natural capital and physical capital have a positive and statistically significant influence, whereas the human capital, financial capital, and social capital of rural households have a negative and statistically significant influence on their income from participation in the project.
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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