The Impact of Policy on Resource Use in Mozambique: A Case Study of Savane
Bibliographic record
Abstract
The study was carried out to analyse the impact of alternative management regimes and changes in sales quantities and prices of Non Timber Forest Products (NTFPs) on the well-being of stakeholders, and on the conservation of the woodlands. A dynamic game theoretic model was developed and used to simulate human population and forest dynamics, harvesting costs, household consumption and prices of forest products. Data from field surveys were used for the simulations. Because stakeholders interests are often in conflict, the chosen modelling approach allows for an evaluation of management regimes. The results indicate that stakeholders and resource conservation social and economic well-being are improved through sound forest management practices. The analysis shows also that regulated forests management regimes in which both profits and social benefits are taken into account are potentially more beneficial to the household sector than the open access regime. Sensitivity analysis indicates that an increase of 100% in the quantity of forest products sold or in the selling prices of NTFPs, ceteris paribus, leads to an increase in per capita benefits of the local communities. However, this increase is not enough to lift the households within the communities above the poverty line of one dollar a day per capita.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".