Sexual Predators, Energy Development, and Conservation in Greater Yellowstone
Bibliographic record
Abstract
In the United States, as elsewhere, a growing debate pits national energy policy and homeland security against biological conservation. In rural communities the extraction of fossil fuels is often encouraged because of the employment opportunities it offers, although the concomitant itinerant workforce is often associated with increased wildlife poaching. We explored possible positive and negative factors associated with energy extraction in the Greater Yellowstone Ecosystem (GYE), an area known for its national parks, intact biological diversity, and some of the New World's longest terrestrial migrations. Specifically, we asked whether counties with different economies-recreation (ski), agrarian (ranching or farming), and energy extractive (petroleum)-differed in healthcare (gauged by the abundance of hospital beds) and in the frequency of sexual predators. The absolute and relative frequency of registered sex offenders grew approximately two to three times faster in areas reliant on energy extraction. Healthcare among counties did not differ. The strong conflation of community dishevel, as reflected by in-migrant sexual predators, and ecological decay in Greater Yellowstone is consistent with patterns seen in similar systems from Ecuador to northern Canada, where social and environmental disarray exist around energy boomtowns. In our case, that groups (albeit with different aims) mobilized campaigns to help maintain the quality of rural livelihoods by protecting open space is a positive sign that conservation can matter, especially in the face of rampant and poorly executed energy extraction projects. Our findings further suggest that the public and industry need stronger regulatory action to instill greater vigilance when and where social factors and land conversion impact biological systems.
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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".