Risk, mobility or population size? Drivers of technological richness among contact-period western North American hunter–gatherers
Bibliographic record
Abstract
Identifying factors that influence technological evolution in small-scale societies is important for understanding human evolution. There have been a number of attempts to identify factors that influence the evolution of food-getting technology, but little work has examined the factors that affect the evolution of other technologies. Here, we focus on variation in technological richness (total number of material items and techniques) among recent hunter-gatherers from western North America and test three hypotheses: (i) technological richness is affected by environmental risk, (ii) population size is the primary determinant of technological richness, and (iii) technological richness is constrained by residential mobility. We found technological richness to be correlated with a proxy for environmental risk-mean rainfall for the driest month-in the manner predicted by the risk hypothesis. Support for the hypothesis persisted when we controlled for shared history and intergroup contact. We found no evidence that technological richness is affected by population size or residential mobility. These results have important implications for unravelling the complexities of technological evolution.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".