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Record W1987707936 · doi:10.1080/01973531003738718

Mental Representation of Familiar Others: The Impact of Occupation, Sex, and Race

2010· article· en· W1987707936 on OpenAlexaff
Kimberley A. Clow, Victoria M. Esses

Bibliographic record

VenueBasic and Applied Social Psychology · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsWestern UniversityUniversity of Ontario Institute of Technology
Fundersnot available
KeywordsPsychologyRace (biology)Task (project management)Prime (order theory)Social psychologyMental representationPerceptionSocial perceptionSocial cognitionRepresentation (politics)CognitionDevelopmental psychologyCognitive psychologyPolitics

Abstract

fetched live from OpenAlex

The current study used a double primed semantic decision task to investigate the role of social group information in mental representations of familiar others. Extrapolating from social role theory, we predicted that social role information would facilitate responding to familiar targets regardless of the specific task at hand. The names of celebrities were used as stimuli, as people know them because of their social role (i.e., their occupation). Primes and targets were matched (or mismatched) on all combinations of sex, race, and occupation. Participants were randomly assigned to task condition: indicating whether the prime and target were (a) of the same sex or not, (b) of the same race or not, or (c) of the same occupation or not. Results indicated that participants responded faster to celebrity prime-target pairs that were matched on occupation regardless of task condition. In addition, participants responded faster to celebrity prime-target pairs that were matched on sex—but only when sex was relevant to the task. Similar findings were not found for race. The implications of these findings for understanding mental representations of familiar others and for person perception 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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.031
GPT teacher head0.410
Teacher spread0.379 · 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

Citations2
Published2010
Admission routes1
Has abstractyes

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