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Fairness in Children's Resource Allocation Depends on the Recipient

2009· article· en· W2144137943 on OpenAlexaff
Chris Moore

Bibliographic record

VenuePsychological Science · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicExperimental Behavioral Economics Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsProsocial behaviorResource allocationPsychologyResource (disambiguation)Social psychologyDevelopmental psychologyEconomicsComputer scienceManagement

Abstract

fetched live from OpenAlex

Sixty-six children between 4.5 and 6 years of age were tested in a resource-allocation game with three different recipients. When the recipient was a friend, children made equitable decisions and shared as much when there was a cost to themselves as when there was no cost. When the recipient was another familiar child who was not a friend, children were less likely to allocate resources to that child. When the recipient was a stranger, children allocated resources as much as with a friend and more than with a nonfriend when there was no cost to themselves. However, when there was a cost to themselves, children treated strangers like nonfriends. These results show that resource-allocation decisions made by young children depend on the recipient. Young children prefer equitable division of resources with friends, treat nonfriends less well, and make prosocial moves with strangers when the cost to self is not high.

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)0.003
metaresearch head score (Gemma)0.012
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 score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.053
GPT teacher head0.395
Teacher spread0.343 · 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

Citations375
Published2009
Admission routes1
Has abstractyes

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