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Record W4200096996 · doi:10.1111/spc3.12652

Collective autonomy: Why groups fight for power and status

2021· article· en· W4200096996 on OpenAlexaff
Frank Kachanoff, Kurt Gray, Richard Koestner, Nour Kteily, Michael J. A. Wohl

Bibliographic record

VenueSocial and Personality Psychology Compass · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsCarleton UniversityMcGill University
Fundersnot available
KeywordsAutonomySocial psychologyPower (physics)DisadvantagedHierarchyPsychologyPosition (finance)Social hierarchyPerspective (graphical)Collective identitySocial identity theoryIdentity (music)Social groupSocial statusGroup (periodic table)Political scienceBusinessPoliticsLaw

Abstract

fetched live from OpenAlex

Abstract People experience “collective autonomy restriction” when they believe other groups want to restrict their own group from freely expressing its social identity and determining its behavior. We review emerging research on the negative consequences of collective autonomy restriction for well‐being, as well as its implications for group members' motivation to fight for their place within social hierarchies. We propose that group members desire two resources tied to having a favorable position within the social hierarchy—structural power (i.e., the ability to influence and resist influence from other groups) and status (being positively valued and perceived as moral by others)—because they believe that having power and status are necessary to secure their group's collective autonomy. We hypothesize that group members anticipate that other groups might restrict their group if they lack the structural power to resist outside influences, or if they are perceived as negative or immoral and worthy of restriction. We apply this power and status perspective of collective autonomy restriction to predict (1) when disempowered groups are most likely to fight against (vs. tolerate) their disadvantaged position and (2) when powerful groups are most likely to relinquish power and acknowledge their transgressions (vs. defensively maintain their privileged position).

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.511
Threshold uncertainty score1.000

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 studies0.0020.001
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 head0.069
GPT teacher head0.396
Teacher spread0.326 · 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.

Study designNot applicable
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

Citations20
Published2021
Admission routes1
Has abstractyes

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