1
Q
Heritability (h²)
A
How much of the differences we see in a trait come from genetic differences
2
Q
Shared environment (C)
A
Influences siblings share (home, parenting style, neighborhood) that make them more alike.
3
Q
Nonshared environment (E)
A
Experiences siblings don’t share (different friends/teachers, random events); also includes some measurement error.
4
Q
Variance
A
How much people differ from each other on a trait.
5
Q
Causation
A
A factor directly produces a change in an outcome.
6
Q
A/C/E model
A
A = genes, C = shared environment, E = nonshared environment; together explain variance in a trait.
7
Q
MZ vs DZ twins
A
MZ share ~100% of genes; DZ share ~50% on average.
8
Q
Why is “correlation ≠ causation”?
A
Two things moving together doesn’t prove one makes the other happen.
9
Q
Naturalistic approach
A
Describe the world as it is, not as we wish it to be.
10
Q
Behaviorism
A
A view that psychology should only study observable behavior, not unobservable stuff.
11
Q
Naturalism vs behaviorism — key difference?
A
Naturalism allows studying unobservables if measured well; behaviorism avoids them.
12
Q
Naturalistic fallacy
A
Saying “it’s natural, so it’s right.” (Is → ought mistake.)
13
Q
Moralistic fallacy
A
Letting what you want to be true decide what you claim is true. (Ought → is mistake.)
14
Q
Confirmation bias
A
Favoring evidence that supports your preferred view and dismissing the rest.
15
Q
GWAS
A
Genome-Wide Association Studies: test whether many small DNA differences together predict an outcome.
16
Q
Polygenic
A
Many genes, each with tiny effects, add up to influence a trait.
17
Q
What is a trade-off?
A
Choosing one benefit usually costs you something else (time, energy, risk).
18
Q
Future discounting
A
Valuing rewards now more than the same reward later.
19
Q
Turkheimer’s 1st Law
A
All human behavioral traits show some genetic influence.
20
Q
Turkheimer’s 2nd Law
A
Shared family environment usually matters less than genes.
21
Q
Turkheimer’s 3rd Law
A
A large chunk of differences isn’t explained by genes or shared family; nonshared environment is big.
22
Q
What does “heritability > 0” actually mean?
A
Genes explain some of the between-person differences; not that genes fully control a trait.
23
Q
Why doesn’t “family resemblance” prove environment?
A
Families share both genes and homes; you need designs that separate them.
24
Q
Gloomy prospect
A
Many outcomes are shaped by random, one-off events we can’t measure well, so prediction is limited.
25
What did Turkheimer warn about simple models?
Simple stats on complex systems give weak, inconsistent results.
26
Do genetic effects mean traits are fixed?
No. Heritable ≠ unchangeable; environments and policies can still matter.
27
Why is variance analysis not the same as causal analysis?
It tells us how much differences are linked to factors, not how those factors make changes.
28
What question does behavioral genetics answer?
Why do people differ from each other? (Not why a single person is the way they are.)
29
Can a trait be highly heritable and still change with policy?
Yes. Means can shift even if variance has genetic parts.
30
What is GWAS trying to find?
DNA patterns that statistically predict outcomes.
31
Are GWAS predictions certain for individuals?
No. They are probabilistic, not destiny.
32
“faster” strategy?
Prefer quick rewards; discount the future more. Earlier maturity, more mating effort, earlier reproduction, more children, thinner resources per child.
33
“slower” strategy?
Willing to wait for bigger future rewards; discount the future less. Later maturity, more somatic and parenting effort, later reproduction, fewer children, deeper investment per child.
34
Life History Theory (LHT)
How people manage trade-offs using environmental cues.
35
Harshness (LHT)
Cues of danger or high mortality in the environment (e.g., violence, frequent deaths).
36
Uncertainty (LHT)
Cues that resources or support are unpredictable (sometimes available, sometimes not).
37
Caregiver reliability
Consistency of caregivers in meeting needs; steady support teaches that long‑term plans can pay off.
38
Future discounting
How much a person values now versus later; higher discounting means preferring immediate rewards.
39
LHT five-step flow
Cues → Future discounting → Strategy (fast/slow) → Trade-offs → Outcomes.
40
Somatic effort
Energy invested in building and maintaining the body (growth, health, skills, learning).
41
Reproductive effort
Energy invested in producing and raising offspring.
42
Parenting effort
Time and energy devoted to caring for existing children.
43
Mating effort
Time and energy spent finding and attracting partners.
44
Quantity–quality trade-off (offspring)
More children with less investment per child versus fewer children with more investment per child.
45
Current vs delayed reproduction
Start having children now versus waiting to build resources and skills.
46
Pubertal timing
Earlier timing aligns with a faster strategy; later timing aligns with a slower strategy.
47
Sexual debut (age at first sex)
Earlier debut aligns with a faster strategy; later debut aligns with a slower strategy.
48
Paternal absence (instability cue)
Often indexes caregiver inconsistency; linked to faster strategies in many studies; consistency matters more than parent gender.
49
Two‑caregiver stability
Consistent support from caregivers; often linked to slower strategies and long‑term planning.
50
Less-to-lose principle
People with fewer expected future payoffs are more willing to take deadly risks now.
51
Winner-takes-all system
A setting where a few winners get most rewards; linked to higher violent competition.
52
Gini coefficient
A 0–1 measure of income inequality; higher values mean more inequality and tend to correlate with higher homicide rates.
53
Inequality–homicide link
More unequal places (higher Gini) tend to show higher homicide rates.
54
Transparent competition
Conflicts over clear resources (money, status, reputation) that can escalate to violence.
55
Distal (ultimate) explanation
The evolutionary reasons a behavior pattern exists (shaped by natural/sexual selection).
56
Sexual selection theory (violence context)
Violent behaviors were favored by evolution because they helped individuals win mates or protect offspring, boosting their chances of passing on genes
57
Institutions (gateways)
Systems like schools, courts, health care, and workplaces that control access to key outcomes (degrees, income, legal status).
58
Institutional stability
How predictable rules and rewards are; more stability means more consistent incentives and outcomes.
59
Delay of gratification
Choosing a larger later reward instead of a smaller now reward.
60
Mischel marshmallow test
Experiment where kids choose 1 treat now or 2 later; used to study delay of gratification.
61
Executive function/control
Mental skills for self-regulation: keep goals in mind, inhibit impulses, and control attention.
62
Goal maintenance
Holding the future goal in mind.
63
Inhibition (self-control)
Blocking the immediate response (e.g., not eating the treat now).
64
Attention deployment
Shifting focus away from temptations to make waiting easier.
65
Longitudinal study
Follows the same people over time to see how early traits relate to later outcomes.
66
Cohort
A group of people of the same age or start year studied together.
67
Within-sibling comparison
Comparing siblings to see if the one with higher self-control does better; reduces household confounds.
68
Moffitt et al. purpose
Test whether early self-control predicts adult health, finances, and crime beyond IQ and SES.
69
Moffitt key finding
Higher self-control in early childhood predicted better adult outcomes even after controlling for IQ/SES and within siblings.
70
Present action vs present-oriented
Acting now can serve future goals (study/train); present-oriented means chasing immediate pleasure instead.
71
Correlation (R)
A number from −1 to +1 that shows direction and strength of a linear relationship; farther from 0 = stronger.
72
Quasi/Natural Experiment
Something in the real world (like a rule change, accident, or event) splits people into groups by chance, and researchers study those groups to see the effects.
73
Antisocial Father Effect
Households with criminal/addicted/volatile fathers show poorer child outcomes than father-absent homes.
74
Trust Cue (Family Support)
Consistent, predictable caregiving builds trust that ‘later rewards’ will arrive, supporting delay of gratification.
75
Discount Rate
The extra amount a later reward must be worth to beat a smaller reward now (e.g., needing much more later to wait).
76
Trust Channel
The ‘do I believe you?’ part of waiting; low trust makes taking the immediate reward rational.
77
Reciprocal Causation
People’s traits and actions shape their environments, which then shape people back.
78
Alfred Binet
Early 1900s developer of school-based intelligence tests to identify students needing support.
79
Binet Test Purpose (Equalizing)
Created to flag children who needed extra help under universal schooling—not to gatekeep.
80
SAT Original Intent
Designed to expand access by spotting talent outside elite pipelines; later used more as a selection tool.
81
General Cognitive Ability (g)
A broad mental ability for reasoning and learning that predicts many life outcomes across domains.
82
Executive Control Components
Goal maintenance, inhibition, and attention control that support delaying gratification.
83
Relative Predictive Value
Judge a tool by how well it predicts compared to other tools, not by whether it is perfect.
84
Holistic Admissions
Review that combines many signals (grades, essays, letters, tests) to predict college success.
85
Objectivity
How fixed and uniform a measure is across readers; test scores are more objective than essays/letters.
86
Broad Abilities
Large skill groups like verbal, quantitative, and spatial that sit under g.
87
Specific (Primary) Abilities
Narrow skills within a broad area (e.g., inductive reasoning under logical/abstract reasoning).
88
g-Loading
How strongly a test shows someone’s overall brain power, not just one small skill.
89
Raven’s Progressive Matrices
A reasoning test with little learned content; often used as a cleaner index of inductive reasoning/g.
90
Inductive Reasoning
Finding patterns and rules from examples (e.g., completing series items).
91
Tests→Abilities→g Mapping
Scores on many tests reflect specific abilities and, partly, the common general factor g.
92
g Share Of Variance (~40–50%)
Rough guide: a large slice of differences on many tests is due to g; the rest is domain-specific.
93
Subtest
A section of a test targeting a specific ability (e.g., verbal analogies).
94
SAT As Proxy For Ability
Colleges often use SAT/ACT because they correlate with ability but avoid the politics of explicit IQ testing.
95
Ritchie & Tucker-Drob (2018) Meta-Analysis
Review of quasi-experiments showing that an extra year of schooling is associated with ~1–5 IQ points higher scores at a given adult age.
96
Engine–Fuel Analogy (Ability vs Education)
Intelligence as the engine and education as the fuel/oil: both matter; the same schooling yields different gains because engines differ.
97
Head Start Fadeout
Early IQ gains from preschool enrichment often diminish by ~2nd–3rd grade, leaving little long-term IQ difference.
98
DHA Supplementation Fadeout
Infant fatty-acid (DHA) supplements show higher IQ around age ~4 but no difference by ~7–8 in follow-ups.
99
Within-Family Design (Sibling/Cousin)
Causal strategy comparing relatives to control shared genes/family environment; often shrinks income–crime links toward zero.
100
Register-Based Study (Nordic)
Research using population registers (e.g., Sweden/Finland) with large samples and linked admin records for crime, income, IQ.
101
Protective Factor (IQ × Risk)
Higher IQ buffers high-risk youth, reducing adult crime compared to equally high-risk peers.
102
Cesarini Et Al. (2023) Lottery Windfalls
Near-random windfalls in Sweden: no meaningful effects on parental crime or offspring crime → one-off money didn’t reduce crime.
103
Akee Et Al. (2010) Casino Payments
Ongoing income boosts to low-income American Indian families: reduced minor offenses in exposed children; no change in moderate/major crimes.
104
Sariaslan Et Al. (2014; 2021) Income–Crime
Sweden/Finland registers: raw low-income ↔ higher violent crime; within-family controls attenuate link ≈ zero (non-causal correlation).
105
Frisell Et Al. (2021) IQ–Crime
Nordic data: lower IQ correlates with more violent crime; within-family controls leave a residual link → some causal role for cognitive ability.
106
Ttofi Et Al. (2016) IQ As Protection
Longitudinal synthesis: among high-risk youth, higher IQ substantially lowers adult criminality (protective effect).
107
Income–Crime Attenuation
The income–violent crime association largely disappears after sibling/cousin controls, implying shared familial factors drive the raw link.
108
File-Drawer Problem (Meta-Analysis)
Bias where null results remain unpublished, inflating pooled effects in meta-analyses.
ISS 215
flashcards
Decks in class (7)
# Cards
