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Record W2133353131 · doi:10.1177/0956797610387613

Social Class, Contextualism, and Empathic Accuracy

2010· article· en· W2133353131 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePsychological Science · 2010
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyClass (philosophy)Social classSocial psychologyTest (biology)EmpathyAssociation (psychology)Developmental psychologyCognitive psychologyEpistemology

Abstract

fetched live from OpenAlex

Recent research suggests that lower-class individuals favor explanations of personal and political outcomes that are oriented to features of the external environment. We extended this work by testing the hypothesis that, as a result, individuals of a lower social class are more empathically accurate in judging the emotions of other people. In three studies, lower-class individuals (compared with upper-class individuals) received higher scores on a test of empathic accuracy (Study 1), judged the emotions of an interaction partner more accurately (Study 2), and made more accurate inferences about emotion from static images of muscle movements in the eyes (Study 3). Moreover, the association between social class and empathic accuracy was explained by the tendency for lower-class individuals to explain social events in terms of features of the external environment. The implications of class-based patterns in empathic accuracy for well-being and relationship outcomes 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.

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 score0.945
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 studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.169
GPT teacher head0.485
Teacher spread0.316 · 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