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Record W4402277258 · doi:10.1037/xge0001617

Cross-cultural conceptions of third-party intervention across childhood.

2024· article· en· W4402277258 on OpenAlexaff
Julia Marshall, Kellen Mermin‐Bunnell, Anton Gollwitzer, Jan Retelsdorf, Paul Bloom

Bibliographic record

VenueJournal of Experimental Psychology General · 2024
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyCross-culturalIntervention (counseling)Developmental psychologySocial psychologyCognitive psychologyAnthropologySociology

Abstract

fetched live from OpenAlex

= 447) across four societies (India, Germany, Uganda, and the United States) reason about third-party intervention. To do so, we measured children's obligation judgments and unstructured descriptions of third-party intervention. Although some cultural differences emerged, 6-year-olds largely considered bystanders as obligated to respond to wrongdoing, regardless of the bystander's social position. In contrast, 9- and 12-year-olds were more likely to exclusively ascribe this social responsibility to people in positions of authority. Despite these age differences, children of all ages generated role-specific descriptions of third-party intervention, with authority figures intervening in distinct ways from peers. For authority figures, children in India and Uganda described third-party intervention as involving corporal punishment or unspecified punishment, whereas children in the United States described such intervention as involving only verbal intervention (i.e., telling someone to stop). For peers, children in all societies described third-party intervention as involving reporting misdeeds to an authority. Collectively, these data show that early conceptualizations of third-party intervention are rooted in shared notions of obligation yet are also subject to cultural and contextual influences. (PsycInfo Database Record (c) 2024 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.595
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.106
GPT teacher head0.588
Teacher spread0.482 · 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.

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

Citations3
Published2024
Admission routes1
Has abstractyes

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