Bibliographic record
Abstract
Humans influence and depend on natural systems worldwide, creating complex societal-ecological feedbacks that make it difficult to assess the long-term sustainability of contemporary human activities. We use ecological niche theory to consider the shortterm (transient) and long-term (equilibrium) effects of improvements in health, agriculture, or efficiency on the abundances of humans, our plant and animal resources, and our natural enemies. We also consider special cases of our model where humans shift to a completely vegetarian diet, or completely eradicate natural enemies. We find that although combinations of health, agriculture, and efficiency improvements tend to support more people and plant resources, they also result in more natural enemies and fewer animal resources. Considering each of these improvements separately reveals that they lead to different, and sometimes opposing, long-term effects. For example, health improvements can reduce pathogen abundances and make it difficult to sustain livestock production, whereas agricultural improvements tend to counterbalance these effects. Our exploratory analysis of a deliberately simple model elucidates trade-offs and feedbacks that could arise from the cascading effects of human activities.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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 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".