Implications of the behavioural immune system for social behaviour and human health in the modern world
Bibliographic record
Abstract
The 'behavioural immune system' is composed of mechanisms that evolved as a means of facilitating behaviours that minimized infection risk and enhanced fitness. Recent empirical research on human populations suggests that these mechanisms have unique consequences for many aspects of human sociality--including sexual attitudes, gregariousness, xenophobia, conformity to majority opinion and conservative sociopolitical attitudes. Throughout much of human evolutionary history, these consequences may have had beneficial health implications; but health implications in modern human societies remain unclear. This article summarizes pertinent ways in which modern human societies are similar to and different from the ecologies within which the behavioural immune system evolved. By attending to these similarities and differences, we identify a set of plausible implications-both positive and negative-that the behavioural immune system may have on health outcomes in contemporary human contexts. We discuss both individual-level infection risk and population-level epidemiological outcomes. We also discuss a variety of additional implications, including compliance with public health policies, the adoption of novel therapeutic interventions and actual immunological functioning. Research on the behavioural immune system, and its implications in contemporary human societies, can provide unique insights into relationships between fitness, sociality and health.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".