Another helping: a plea for an interdisciplinary perspective on the role of kin over the life course
Bibliographic record
Abstract
Having kin and living together with kin influence the individual life course, including a person’s marriage, reproductive career, and survival. A wide range of mechanisms are involved in connecting these life course transitions to support and competition between kin, as well as to characteristics of the family environment. How kin affect the life course is perceived differently in evolutionary anthropology than in the social sciences, and these perspectives are seldom integrated into research. In the present article, we review predictions of the influence of in-law relatives on fertility and mortality presented in selected studies. We will then discuss their explanatory power by discussing the influence of the mother-in-law on the mortality of reproductive females in the historical populations of the Krummhorn region in Germany (1720–1874) and the St. Lawrence Valley in Quebec, Canada (1670–1799). Social science studies tend to emphasize the role of kin in economic and social resource availability, and especially the family characteristics that are relevant in providing, accessing, and dividing resources. In contrast, evolutionary anthropology tends to emphasize the evolved inclinations of kin to support as well as to compete with each other. On the one hand, we argue that the social sciences would benefit from integrating the evolutionary theory of human behavior. On the other hand, evolutionary anthropology would benefit from the comprehensive acknowledgment of the socio-environmental factors in population since these may mask evolved.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.023 |
| Scholarly communication | 0.005 | 0.014 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 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".