Taboos and Forest Governance: Informal Protection of Hot Spot Dry Forest in Southern Madagascar
Bibliographic record
Abstract
In the dry forest of southern Madagascar, a region of global conservation priority, formally protected areas are nearly totally absent. We illustrate how the continued existence of unique forest habitats in the Androy region is directly dependent on informal institutions, taboos, regulating human behavior. Qualitative interviews to map and analyze the social mechanisms underlying forest protection have been combined with vegetation analyses of species diversity and composition. Of 188 forest patches, 93% were classified as protected, and in Southern Androy all remaining forest patches larger than 5 ha were protected. Eight different types of forests, with a gradient of social fencing from open access to almost complete entry prohibitions, were identified. Transgressions were well enforced with strong sanctions of significant economic as well as religious importance. Analyses of species diversity between protected and unprotected forests were complicated because of size differences and access restrictions. However, since, for example, in southern Androy >90% of the total remaining forest cover is protected through taboos, these informal institutions represent an important, and presently the only, mechanism for conservation of the highly endemic forest species. We conclude that social aspects, such as local beliefs and legitimate sanctioning systems, need to be analyzed and incorporated along with biodiversity studies for successful conservation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".