An Experimental Investigation of the Functional Hypothesis and Evolutionary Advantage of Stone-Tipped Spears
Bibliographic record
Abstract
Stone-tipped weapons were a significant innovation for Middle Pleistocene hominins. Hafted hunting technology represents the development of new cognitive and social learning mechanisms within the genus Homo, and may have provided a foraging advantage over simpler forms of hunting technology, such as a sharpened wooden spear. However, the nature of this foraging advantage has not been confirmed. Experimental studies and ethnographic reports provide conflicting results regarding the relative importance of the functional, economic, and social roles of hafted hunting technology. The controlled experiment reported here was designed to test the functional hypothesis for stone-tipped weapons using spears and ballistics gelatin. It differs from previous investigations of this type because it includes a quantitative analysis of wound track profiles and focuses specifically on hand-delivered spear technology. Our results do not support the hypothesis that tipped spears penetrate deeper than untipped spears. However, tipped spears create a significantly larger inner wound cavity that widens distally. This inner wound cavity is analogous to the permanent wound cavity in ballistics research, which is considered the key variable affecting the relative 'stopping power' or 'killing power' of a penetrating weapon. Tipped spears conferred a functional advantage to Middle Pleistocene hominins, potentially affecting the frequency and regularity of hunting success with important implications for human adaptation and life history.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".