Colonist Household Decisionmaking and Land-Use Change in the Amazon Rainforest: An Agent-Based Simulation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
An agent-based model was developed as a tool designed to explore our understanding of spatial, social, and environmental issues related to land-use/cover change. The model focuses on a study site in a region of the Amazon frontier, characterized by the development of family farms on 100-ha lots arranged along the Transamazon highway and a series of side roads, west of Altamira, Brazil. The model simulates the land-use behaviour of farming households on the basis of a heuristic decisionmaking strategy that utilizes burn quality, subsistence requirements, household characteristics, and soil quality as key factors in the decisionmaking process. Farming households interact through a local labour pool. The effects of the land-use decisions made by households affect the land cover of their plots and ultimately that of the region. This paper describes this model, referred to as LUCITA, and presents preliminary results showing land-cover changes that compare well with observed land-use and land-cover changes in the region.
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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 | 0.001 | 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