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Record W2270416027 · doi:10.1371/journal.pone.0147325

Thinking Big or Small: Does Mental Abstraction Affect Social Network Organization?

2016· article· en· W2270416027 on OpenAlexaff
Chantal Bacev-Giles, Johanna Peetz

Bibliographic record

VenuePLoS ONE · 2016
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsCarleton University
Fundersnot available
KeywordsMindsetAffect (linguistics)AbstractionCategorizationPsychologySocial groupCognitionSocial psychologySocial cognitionDevelopmental psychologyComputer scienceCommunication

Abstract

fetched live from OpenAlex

Four studies examined how mental abstraction affects how people perceive their relationships with other people, specifically, how these relationships may be categorized in social groups. We expected that individuals induced to think abstractly would report fewer more global social groups, compared to those induced to think concretely, who would report more specific groups. However, induced abstract mindset did not affect how people structured their social groups (Study 2-4), despite evidence that the mindset manipulation changed the level of abstraction in their thoughts (Study 3) and evidence that it changed how people structured groups for a control condition (household objects, Study 4). Together, these studies suggest that while the way people organize their relationships into groups is malleable; cognitive abstraction does not seem to affect how people categorize their relationships into social groups.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.122
GPT teacher head0.353
Teacher spread0.232 · 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 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
Published2016
Admission routes1
Has abstractyes

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