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Record W2067786881 · doi:10.1126/science.1178336

Intergenerational Wealth Transmission and the Dynamics of Inequality in Small-Scale Societies

2009· article· en· W2067786881 on OpenAlexaff
Monique Borgerhoff Mulder, Samuel Bowles, Tom Hertz, Adrian V. Bell, Jan Beise, Greg Clark, Ila Fazzio, Michael Gurven, Kim Hill, Paul L. Hooper, William Irons, Hillard Kaplan, Donna L. Leonetti, Bobbi S. Low, Frank W. Marlowe, Richard McElreath, Suresh Naidu, David A. Nolin, Patrizio Piraino, Rob Quinlan, Eric Schniter, Rebecca Sear, Mary K. Shenk, Eric Alden Smith, Christopher von Rueden, Polly Wiessner

Bibliographic record

VenueScience · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational and Educational Inequality Studies
Canadian institutionsStatistics Canada
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute on Aging
KeywordsInequalityAgrarian societyForagingLivelihoodEconomicsPopulationScale (ratio)AgricultureDemographic economicsEthosEconomic geographyDevelopment economicsGeographyEcologySociologyBiologyPolitical scienceDemography

Abstract

fetched live from OpenAlex

Small-scale human societies range from foraging bands with a strong egalitarian ethos to more economically stratified agrarian and pastoral societies. We explain this variation in inequality using a dynamic model in which a population's long-run steady-state level of inequality depends on the extent to which its most important forms of wealth are transmitted within families across generations. We estimate the degree of intergenerational transmission of three different types of wealth (material, embodied, and relational), as well as the extent of wealth inequality in 21 historical and contemporary populations. We show that intergenerational transmission of wealth and wealth inequality are substantial among pastoral and small-scale agricultural societies (on a par with or even exceeding the most unequal modern industrial economies) but are limited among horticultural and foraging peoples (equivalent to the most egalitarian of modern industrial populations). Differences in the technology by which a people derive their livelihood and in the institutions and norms making up the economic system jointly contribute to this pattern.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.037
GPT teacher head0.353
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations498
Published2009
Admission routes1
Has abstractyes

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