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Evolution and Family Life Sex and reproductive variance: Males: bigger gamble; hi risk/hi reward Females: better odds, lower payoff.

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Presentation on theme: "Evolution and Family Life Sex and reproductive variance: Males: bigger gamble; hi risk/hi reward Females: better odds, lower payoff."— Presentation transcript:

1 Evolution and Family Life Sex and reproductive variance: Males: bigger gamble; hi risk/hi reward Females: better odds, lower payoff

2 Trivers/Willard Hypothesis Good conditions: invest in boys Not so good conditions: invest in girls Humans? – Medieval Portugal church records – more boys conceived during years when rains were good (Jolly, 1999, p. 122) – High income mothers breastfeed sons more than daughters, vice-versa low income. – IBI longer for hi income after son; vice-versa for low income – However, other contemporary studies have found mixed or negative results

3 Primate infanticide Sara Hrdy: Langur Monkey infanticide Also documented in lions and gorillas. New male has limited time as alpha, no time to spend on non-genetic offspring. Adaptive value of female promiscuity: “seeds of confusion” theory

4 ©John Wiley & Sons, Inc Huffman: Psychology in Action (8e) Risks of step-parenting. Note: Violent step parents represent less than 1% of step families Cross-culturally (60 different societies; Daly & Wilson, 1988) most common reasons for killing or abandonment of newborns/infants: Questionable paternity; low reproductive value of infant (weak, sick, abnormal; poor maternal circumstances (unmarried, little family/social support; poor resources)

5 Birth vs. step children: education, health; nutrition Anne Case – economist at Princeton Plight of Cinderella (children and step mothers) Sig decrease in food expenditure when non-bio mother in home Children raised with non-bio mother sig less educational attainment compared to bio mothers In mixed families, exclusively non-bio offspring that suffer reduced educational levels (see graph left) Non-bio mother: fewer visits to doc, dentist; reduced expenditures on fruits, vegetables, milk, more on alcohol, tobacco.

6 Sibling rivalry Mom is equally related to all her offspring Sibs are 100% related to themselves; only half (genetically) related to each other All things being equal (which often they aren’t) Mom has natural incentive to be “fair” to offspring Each sib has incentive to extract more resources from Mom then sibs “That’s not fair”

7 Sexually Dimorphic Maturation Rates Put simply – girls mature faster than boys. Why? Females: Secondary sexual development precedes gametogenesis (fertility); they look sexually mature before they are fully mature (probably more exaggerated in ancestral past then today, in most traditional societies there’s 2-3 year period of infertility after onset of secondary sexual traits) Boys: vice-versa 14 year-old boy vs. 14 year old girl

8 Sexually Dimorphic Maturation Rates Males: Evolved divergent mating strategies: Early maturing – Alpha strategy; more short-term mating opportunities. Late maturing -- stealth strategy; sexually fertile but physically non-threatening. Females: “Practice” for mothering skills Evidence mixed: Faster maturing boys = higher status, more popular, slower maturing boys = more creative Girls do more babysitting, child care, but does this mean maturation rates selected for this purpose, jury still out.

9 Future stability and female maturation rates K vs. r reproduction strategies: unstable future – live fast, reproduce early and often (r) Factors related to faster maturation rate in human females: (1) domestic instability and stress; (2) father absence; (3) lack of grandparental figures, esp grandfathers; (4) economic deprivation. Male investment unreliable; reproduce early while familial support present

10 Sex ratio, poverty, and reproduction Operational sex ratio: ratio of sexually active males to sexually receptive females. <1; more females than males; intense female mate competition. Few investing males; marital instability; more single moms; promiscuity, etc >1; more males than females; intense male mate competition. Low status males lose out; greater marital stability; higher crime. For lower socio-eco females (dashed and dotted lines) as osr decreases (fewer males) birth rate increases for younger women. But higher s-e women have lower birth rate at younger ages as osr decreases and higher birth rate at older ages. With few investing males, poor women “speed up” life history; rich women “slow down.” Ref: Chipman & Morris, 2013 study

11 Crazy Bastard Hypo Young male propensity for risk-taking: signal of formidabilty. Signal to whom? Male rivals and allies Males who take risks are perceived as taller, bigger, more muscular more prone to violence. Turn off to females as long-term mate, but may be desirable as “protector” in dangerous environment. Absence of fathers usually produces more violence among boys. Does propensity toward risk taking increase if boys do not see many older male role models around? In other words, where there is long-term mating (evidenced by fathers) a boy's mating strategy shifts toward attracting long-term mates and thus reduced risk-taking. Self-Reinforcing Cycle: violent social context -> risk taking males for allies -> less long term mating -> female preference for formidable male (genetics, protection) -> more risk taking -> more violence

12 Parental Grief Correlates with reproductive value curve for children more so than just age. Tends to peak at early adolescence. Max investment at threshold of reproductive payoff. Matches life history pattern of traditional hunter- gatherers, more so than contemporary life history curves.

13 Demographic Transition DT: Wealthy countries have below replacement birthrates Evo paradox. Why? Greater investment per child to maintain status Status seeking conflicts with parental investment However, in long run higher investment reduces fitness! Genetic/personality factors important: Extro males and agreeable females more fertile High status males more fertile; high status females less fertile.

14 Religion & Fertility source: last three slides see* Data Source: Dominik Enste, Institut der deutschen Wirtschaft Köln 2007

15 Swiss Census 2000 Denominational category (CFR) Births per woman % academic education % higher occupational class Hinduism* 2,79 (1) 17,0% (12)7,4% (14) Islam* 2,44 (2) 11,4% (15)6,1% (15) Jewish 2,06 (3) 42,7% (1)42,4% (1) Other (smaller) Protestant 2,04 (4) 20,1% (5)19,2% (6) New Pietism / Evangelical 2,02 (5) 19,2% (6)17,9% (8) Pentecostal 1,96 (6) 17,1% (11)15,7% (10) Other (smaller) Christian 1,82 (7) 39,1% (2)31,8% (2) Didn’t answer 1,74 (8) 19,1% (7)5,3% (16) Christian-Orthodox* 1,62 (9) 18,0% (10)9,8% (13) Swiss Average1,4319,2%19,6% Buddhist* 1,42 (10) 20,3% (4)13,4% (11) Roman-Catholic 1,41 (11) 16,8% (13)18,5% (7) New Apostolic 1,39 (12) 13,9% (14)17,6% (9) Reformed Protestant 1,35 (13) 18,9% (8)22,2% (4) Yehova’s Witnesses 1,24 (14) 6,8% (16)11,2% (12) Christian-Catholic 1,21 (15) 18,4% (9)22,2% (5) Non-affiliated 1,11 (16) 30,6% (3)26,7% (3) r / Spearman Rank Correl.0,054-0,269

16 Religiosity is offering POTENTIALS to culturally diverse, reproductive strategies  We still found NO demographically successful non- religious population! Hutterites, Haredim, Old Order Amish etc. Shakers Non- Affiliated USA, China, France, Sweden, Austria etc.

17 *Why are the Non-Religious lacking Children Exploring the Evolutionary Adaptivity of Religion Dr. Michael Blume ( )www.blume-religionswissenschaft.de „Philosophical Anthropology of Religion“, Wuppertal University, March 2014


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