Is there a trade‐off between fertility and longevity? A comparative study of women from three large historical databases accounting for mortality selection
Bibliographic record
Abstract
Frontier populations provide exceptional opportunities to test the hypothesis of a trade-off between fertility and longevity. In such populations, mechanisms favoring reproduction usually find fertile ground, and if these mechanisms reduce longevity, demographers should observe higher postreproductive mortality among highly fertile women. We test this hypothesis using complete female reproductive histories from three large demographic databases: the Registre de la population du Québec ancien (Université de Montréal), which covers the first centuries of settlement in Quebec; the BALSAC database (Université du Québec à Chicoutimi), including comprehensive records for the Saguenay-Lac-St-Jean (SLSJ) in Quebec in the nineteenth and twentieth centuries; and the Utah Population Database (University of Utah), including all individuals who experienced a vital event on the Mormon Trail and their descendants. Together, the three samples allow for comparisons over time and space, and represent one of the largest set of natural fertility cohorts used to simultaneously assess reproduction and longevity. Using survival analyses, we found a negative influence of parity and a positive influence of age at last child on postreproductive survival in the three populations, as well as a significant interaction between these two variables. The effect sizes of all these parameters were remarkably similar in the three samples. However, we found little evidence that early fertility affects postreproductive survival. The use of Heckman's procedure assessing the impact of mortality selection during reproductive ages did not appreciably alter these results. We conclude our empirical investigation by discussing the advantages of comparative approaches.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".