Bibliographic record
Abstract
The evolutionary emergence of the human species in a predatory niche has often been seen as the root cause of all the bloodshed and aggression that besets the human condition, particularly religious violence. This is certainly the case with the thought of Walter Burkert and René Girard, both of whom argue that, because the earliest humans were hunters, collective murder or “sacrifice” is the founding practice of all religions. Consequently, for them, the dark specter of bloodshed and violence lies at the heart of all religious thought. However, Burkert’s and Girard’s accounts rest on unexamined and problematic assumptions concerning predation, hunting and violence. Specifically, their characterization of predation and prehistoric hunting peoples as intrinsically aggressive is both ecologically and anthropologically naïve and ill-informed. By contrast, the ecologist Paul Shepard’s empirically informed account challenges not only the link between aggression and predation but also that between hunting and sacrifice. He argues that, far from producing a “killer ape,” the evolutionary transition of early hominids into a predatory niche resulted in a “tender carnivore” with an increased capacity for empathy with other humans and animals. Furthermore, he argues that blood sacrifice, far from lying with hunting at the dawn of human history, in fact emerged with the advent of agriculture and domestication. Thus, in challenging the commonly held association between hunting, violence and sacrifice, Shepard is asking us to rethink our understanding of the sacramentality of hunting, nature and life itself.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".