Bibliographic record
Abstract
The tropical deforestation literature advocates multi-agent enquiry in recognition that key dynamics arise from inter-agent interactions. Studies of tropical forest-cover gain have lagged in this respect. This article explores the roles and key aspects of interactions shaping natural forest regeneration and active reforestation in Eastern Panama since 1990. It employs household surveys of agricultural landholders, interviews with community forest-restoration organisations, archival analysis of plantation reforestation interests, satellite image analysis of forest-cover change, and the consideration of State reforestation policies. Forest-cover gain reflected a convergence of interests and land-use trends amongst agents. Low social and economic costs of sustained interaction and organisation enabled extensive forest-cover gain, but low transaction costs did not. Corporate plantation reforestation rose to the fore of regional forest-cover gain via opportunistic land sales by ranchers and economic subsidies indicative of a State preference for autonomous, self-organising forest-cover gain. This reforestation follows a recent history of neoliberal frontier development in which State-backed loggers and ranchers similarly displaced agriculturalists. Community institutions, long neglected by the State, struggled to coordinate landholders and so effected far less forest-cover gain. National and international commitments to tropical forest restoration risk being similarly characterised as ineffective by a predominance of industrial plantation reforestation without greater State support for community forest management.
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How this classification was reachedexpand
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) | 0.001 | 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 teacher head, 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".