Ecologically Unequal Exchange, World Polity, and Biodiversity Loss
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
There have been a few cross-national studies published that examine the determinants of threatened mammal species. However, these studies neglect insights from both ecologically unequal exchange theory and world polity theory. We seek to address this gap in the literature using cross-national data for a sample of 74 nations to construct negative binomial regression models with the number of threatened mammal species as the dependent variable. In doing so, we find substantial support for ecologically unequal exchange theory that flows of primary sector exports from poor to rich nations are associated with higher levels of threatened mammals in poor nations. We also find support for world polity theory that environmental non-governmental organizations are associated with lower levels of threatened mammals in poor nations. We conclude with a discussion of the findings, some policy implications, and possible directions for future research.
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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 | 0.000 | 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 | 0.001 |
| 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