Land-use poverty traps identified in shifting cultivation systems shape long-term tropical forest cover
Bibliographic record
Abstract
In this article we illustrate how fine-grained longitudinal analyses of land holding and land use among forest peasant households in an Amazonian village can enrich our understanding of the poverty/land cover nexus. We examine the dynamic links in shifting cultivation systems among asset poverty, land use, and land cover in a community where poverty is persistent and primary forests have been replaced over time--with community enclosure--by secondary forests (i.e., fallows), orchards, and crop land. Land cover change is assessed using aerial photographs/satellite imagery from 1965 to 2007. Household and plot level data are used to track land holding, portfolios, and use as well as land cover over the past 30 y, with particular attention to forest status (type and age). Our analyses find evidence for two important types of "land-use" poverty traps--a "subsistence crop" trap and a "short fallow" trap--and indicate that the initial conditions of land holding by forest peasants have long-term effects on future forest cover and household welfare. These findings suggest a new mechanism driving poverty traps: insufficient initial land holdings induce land use patterns that trap households in low agricultural productivity. Path dependency in the evolution of household land portfolios and land use strategies strongly influences not only the wellbeing of forest people but also the dynamics of tropical deforestation and secondary forest regrowth.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".