Required parental investment and mating patterns: A quantitative analysis in the context of evolutionarily stable strategies
| Autor: | Heather J. Downey, Myles Derieg, Glenn Geher |
|---|---|
| Rok vydání: | 2004 |
| Předmět: |
Male
Reproductive Behavior Context (language use) Models Psychological Biology Psychology Social Sex Factors Gene Frequency Sociobiology Genetics Quantitative assessment Humans Mating Parental investment Ecology Evolution Behavior and Systematics Demography Models Genetic Parenting Ecology Psychological research Courtship Biological Evolution Quantitative model Phenotype Quantitative analysis (finance) Anthropology Costs and Cost Analysis Female |
| Zdroj: | Biodemography and Social Biology. 51:54-70 |
| ISSN: | 1948-5573 1948-5565 |
| DOI: | 10.1080/19485565.2004.9989083 |
| Popis: | Much social psychological research has been dedicated to understanding mating strategies from the standpoint of genetic-fitness payout (e.g., Simpson and Gangestad, 2000). The current work is designed to provide a coherent, quantitative model for predicting different classes of mating strategies in both males and females. Specifically, the framework developed in this paper is an elaboration of Dawkins' (1989) quantitative assessment of different male and female mating strategies. Dawkins suggests that the prevalence of different strategies employed should be predictable in terms of evolutionary stable strategies. In the current work, a quantitative analysis predicting the prevalence of different mating strategies within each sex was conducted. The mathematical functions derived suggest that variability in the costs associated with raising offspring affects the expected prevalence of mating strategies differently for males and females. According to the present model, variability in female strategies should be less affected by changes in parental investment (PI) than variability in male strategies. Important predictions regarding male and female mating strategies across cultures are discussed. |
| Databáze: | OpenAIRE |
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