Bibliographic record
Abstract
The killing of Cecil the lion (Panthera leo) ignited enduring and increasingly global discussion about trophy hunting. Yet, policy debate about its benefits and costs focuses only on the hunted species and biodiversity, not the unique behaviour of hunters. Some contemporary recreational hunters from the developed world behave curiously, commonly targeting ‘trophies’: individuals within populations with large body or ornament size, as well as rare and/or inedible species, like carnivores. Although contemporary hunters have been classified according to implied motivation (i.e. for meat, recreation, trophy or population control, as well the ‘multiple satisfactions’ they seek while hunting (affiliation, appreciation, achievement; an evolutionary explanation of the motivation underlying trophy hunting (and big-game fishing) has never been pursued. Too costly (difficult, dangerous) a behaviour to be common among other vertebrate predators, we postulate that trophy hunting is in fact motivated by the costs hunters accept. We build on empirical and theoretical contributions from evolutionary anthropology to hypothesize that signalling these costs to others is key to understanding, and perhaps influencing, this otherwise perplexing activity.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.003 |
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; both teacher heads agree on what is shown here.
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".