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Record W1573959190 · doi:10.1177/1088868315589475

Mechanisms of Identity Conflict

2015· review· en· W1573959190 on OpenAlexaff
Jacob B. Hirsh, Sonia K. Kang

Bibliographic record

VenuePersonality and Social Psychology Review · 2015
Typereview
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSocial psychologyGroup conflictNormativePsychologySocial identity theoryIdentity (music)Action (physics)Social identity approachSocial groupSocial anxietySocial conflictCollective identityAnxietyPolitical science

Abstract

fetched live from OpenAlex

Social identities are associated with normative standards for thought and action, profoundly influencing the behavioral choices of individual group members. These social norms provide frameworks for identifying the most appropriate actions in any situation. Given the increasing complexity of the social world, however, individuals are more and more likely to identify strongly with multiple social groups simultaneously. When these groups provide divergent behavioral norms, individuals can experience social identity conflict. The current manuscript examines the nature and consequences of this socially conflicted state, drawing upon advances in our understanding of the neuropsychology of conflict and uncertainty. Identity conflicts are proposed to involve activity in the Behavioral Inhibition System, which in turn produces high levels of anxiety and stress. Building upon this framework, four strategies for resolving identity conflict are reviewed.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.223
GPT teacher head0.469
Teacher spread0.245 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations205
Published2015
Admission routes1
Has abstractyes

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