What drives the evolution of hunter–gatherer subsistence technology? A reanalysis of the risk hypothesis with data from the Pacific Northwest
Bibliographic record
Abstract
Recent studies have suggested that the decisions that hunter-gatherers make about the diversity and complexity of their subsistence toolkits are strongly affected by risk of resource failure. However, the risk proxies and samples employed in these studies are potentially problematic. With this in mind, we retested the risk hypothesis with data from hunter-gatherer populations who lived in the northwest coast and plateau regions of the Pacific Northwest during the early contact period. We focused on these populations partly because the northwest coast and plateau differ in ways that can be expected to lead to differences in risk, and partly because of the availability of data for a wide range of risk-relevant variables. Our analyses suggest that the plateau was a more risky environment than the northwest coast. However, the predicted differences in the number and complexity of the populations' subsistence tools were not observed. The discrepancy between our results and those of previous tests of the risk hypothesis is not due to methodological differences. Rather, it seems to reflect an important but hitherto unappreciated feature of the relationship between risk and toolkit structure, namely that the impact of risk is dependent on the scale of the risk differences among populations.
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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 | 0.001 | 0.015 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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".