The Influence of Nonrandom Mating on Population Growth
Bibliographic record
Abstract
When nonrandom mating alters offspring numbers or the distribution of offspring phenotypes, it has the potential to impact the population growth rate. Similarly, sex-specific demographic parameters that influence the availability of mating partners can leave a signature on the population growth rate. We develop a general framework to explore how mating patterns and sex differences influence the population growth rate. We do this by constructing a two-sex integral projection model to explore ways in which altering the mating behavior from random to nonrandom mating (assortative, disassortative, or selection for size) and altering demographic parameters in one or both sexes (growth, survival, and parental contribution to offspring phenotype) affect the population growth rate. We demonstrate our framework using data from a population of Columbian ground squirrels. Our results suggest that the population growth rate is substantially affected when nonrandom mating is linked to sex differences in demographic parameters or parental contributions to offspring phenotype, but interestingly, the effect of the mating pattern alone is rather small. Our results also suggest that the population growth rate of Columbian ground squirrels would increase with the degree of disassortative mating and with the degree of the mating advantage of large individuals.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".