Domestication is not an ancient moment of selection for prosociality: Insights from dogs and modern humans
Bibliographic record
Abstract
Domestication is often portrayed as a long-past event, at times even in archaeological literature. The term domestication is also now applied to other processes, including human evolution. In such contexts, domestication means selection for friendliness or prosociality and the bodily results of such selective choices. Both such perspectives are misleading. Using dogs and modern humans as entry points, this paper explores why conceiving of domestication as a threshold event consisting of selection for prosociality is both incomplete and inaccurate. Domestication is an ongoing process, not a moment or an achievement. Selection in breeding, including for prosociality, is a part of many domestication histories, but it alone does not sustain this process over multiple generations. Further, much selection in domestication has little to do with human intention. Care, taming, commensalism, material things, and places are critical in carrying domestic relationships forward.
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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) | 0.000 | 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".