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Record W4394917011 · doi:10.1037/xge0001573

How theory of mind leads to positive first impressions.

2024· article· en· W4394917011 on OpenAlexafffund
Chloe C. Hudson, Mark A. Sabbagh, Kate L. Harkness

Bibliographic record

VenueJournal of Experimental Psychology General · 2024
Typearticle
Languageen
FieldNeuroscience
TopicCognitive Science and Education Research
Canadian institutionsQueen's University
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health ResearchMcLean Hospital
KeywordsPsychologyEpistemologySocial psychologyPsychoanalysisCognitive psychologyPhilosophy

Abstract

fetched live from OpenAlex

A common conjecture is that social success relies on "theory of mind"-the everyday skill of imputing mental states to others. We test the hypothesis that individuals with stronger theory of mind skills and motivation garner more positive first impressions because of how they interact with others. Participants included 334 young adults who were paired with a peer for a first-time meeting. Dyads completed a cooperative Lego-building task, which was videotaped and later coded for behavioral manifestations of theory of mind by independent raters. Theory of mind accuracy and motivation were assessed with validated laboratory tasks and a self-report questionnaire, respectively. First impressions were assessed based on partner's ratings of participant likeability, enjoyment of the interaction, and changes in positive affect. Results of actor-partner interdependence mediation models revealed that the associations between theory of mind and first impressions are indirect and mediated through behaviors. Specifically, participants with stronger theory of mind demonstrated greater cognitive sensitivity and pragmatic conversational skills. However, only cognitive sensitivity subsequently predicted more favorable first impressions. This research shows that social-cognitive skills can affect others' social impressions through their behavioral manifestations. (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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.617

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.097
GPT teacher head0.456
Teacher spread0.359 · 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 designBench or experimental
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 routes2
Has abstractyes

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