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Record W2130339726 · doi:10.1037/a0020092

Having less, giving more: The influence of social class on prosocial behavior.

2010· article· en· W2130339726 on OpenAlexafffund
Paul K. Piff, Michael W. Kraus, Stéphane Côté, Bonnie Hayden Cheng, Dacher Keltner

Bibliographic record

VenueJournal of Personality and Social Psychology · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaJohn Templeton Foundation
KeywordsProsocial behaviorPsychologySocial psychologySocial classModerationSocioeconomic statusFeelingDevelopmental psychologyCompassionWelfareUpper classDemography

Abstract

fetched live from OpenAlex

Lower social class (or socioeconomic status) is associated with fewer resources, greater exposure to threat, and a reduced sense of personal control. Given these life circumstances, one might expect lower class individuals to engage in less prosocial behavior, prioritizing self-interest over the welfare of others. The authors hypothesized, by contrast, that lower class individuals orient to the welfare of others as a means to adapt to their more hostile environments and that this orientation gives rise to greater prosocial behavior. Across 4 studies, lower class individuals proved to be more generous (Study 1), charitable (Study 2), trusting (Study 3), and helpful (Study 4) compared with their upper class counterparts. Mediator and moderator data showed that lower class individuals acted in a more prosocial fashion because of a greater commitment to egalitarian values and feelings of compassion. Implications for social class, prosocial behavior, and economic inequality are discussed.

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)0.002
metaresearch head score (Gemma)0.008
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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.054
GPT teacher head0.411
Teacher spread0.357 · 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

Citations1,469
Published2010
Admission routes2
Has abstractyes

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