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Record W3160889095 · doi:10.3167/cont.2021.090103

The Relationship between Dimensions of Collective Action, Introversion/ Extroversion, and Collective Action Endorsement among Women

2021· article· en· W3160889095 on OpenAlexaff
Adrianna Tassone, Mindi D. Foster

Bibliographic record

VenueContention · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsExtraversion and introversionCollective actionSocial psychologyPsychologyAction (physics)PersonalityTraitBig Five personality traitsPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Given the psychosocial benefits of collective action for minority group members, we explored how the personality trait introversion/extroversion may contribute to current understandings of what motivates collective action among women. Dimensions of collective action that are consistent with introversion (e.g., low risk) were expected to predict greater endorsement of collective action among introverts, whereas dimensions consistent with extroversion (e.g., public) were expected to predict greater endorsement among extroverts. One hundred and seventy-nine women completed an online questionnaire, and regression analyses showed that among introverts, collective action rated lower in risk and social cost, but higher in effectiveness and formality predicted greater endorsement. Among extroverts, collective action rated as more public (vs. private) predicted greater endorsement. The implications of utilizing personality profiles to enhance collective action 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 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)0.006
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.089
GPT teacher head0.353
Teacher spread0.263 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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