MétaCan
Menu
Back to cohort
Record W4407762095 · doi:10.1037/dev0001931

Prosocial responses to diverse needs in urban Canadian and rural Tzotzil Maya children.

2025· article· en· W4407762095 on OpenAlexfundaboutno aff
Kristen A. Dunfield, Radu Urian, Nasim Tavassoli, Astrid Kleis

Bibliographic record

VenueDevelopmental Psychology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaFonds de Recherche du Québec-Société et Culture
KeywordsProsocial behaviorPsychologyMayaDevelopmental psychologyRural areaChild developmentSocial psychologyGeography

Abstract

fetched live from OpenAlex

This research examined 3- to 6-year-old's prosocial responses to an unfamiliar experimenter demonstrating diverse needs (instrumental, material, and emotional) in structured tasks across two distinct cultural contexts (urban Canada/Canadian vs. rural Mexico/Tzotzil Maya). Two hundred eighty participants were recruited from preschools in Zinacantán, Mexico (100% Tzotzil Maya), and Montréal, Canada (70% European descent). We compared responses to instrumental, material, and emotional needs across experimental (need present) and control (need absent) conditions. In both cultural contexts, prosociality was responsive to need. However, Canadian children were more likely to respond prosocially than the Tzotzil Maya children across all three needs. In addition, consistent with past research, we found that prosocial responses increased with age. Across the two cultural contexts, we observed both similarities (e.g., the relative frequency of responding to the various needs) and differences (e.g., the effect of task on prosocial responding to instrumental and emotional needs). Taken together, these results highlight the importance of considering the nuanced role of culture in the development of diverse prosocial behaviors. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.236
Threshold uncertainty score0.942

Codex and Gemma teacher scores by category

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

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 head0.016
GPT teacher head0.336
Teacher spread0.320 · 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 teacher head, 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
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueDevelopmental PsychologySame topicEarly Childhood Education and DevelopmentFrench-language works237,207