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Record W2045640851 · doi:10.1177/0146167211426729

Stigma Building Blocks

2011· article· en· W2045640851 on OpenAlexafffund
Sonia K. Kang, Michael Inzlicht

Bibliographic record

VenuePersonality and Social Psychology Bulletin · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaNational Academy of EducationSpencer Foundation
KeywordsPsychologySocial psychologyStigma (botany)

Abstract

fetched live from OpenAlex

Gaining an understanding of intergroup relations and outgroup rejection is an important childhood development. Children learn about rejection by outgroups via their own experiences and external instruction. A comparison of the impact of experience and instruction on first-, third-, and fifth-grade children's evaluations of rejection by outgroups in a minimal-groups paradigm suggests that the relative impact of experience and instruction differs as children age. In Study 1, younger children were more influenced by instruction, and older children were more influenced by what they experienced for themselves. In Study 2, younger children were more influenced by instruction, even when that instruction conflicted with what they experienced; older children were more influenced by their own experiences, even when those experiences contradicted what they were told to expect. These findings suggest that children begin learning about outgroup rejection through instruction but start to rely more on their own experiences as they age.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.057
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0050.004
Scholarly communication0.0040.004
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0570.007

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 head0.093
GPT teacher head0.375
Teacher spread0.281 · 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 designTheoretical or conceptual
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

Citations23
Published2011
Admission routes2
Has abstractyes

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