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Record W2130442619 · doi:10.1525/sop.2006.49.2.217

The Emotional Contradictions of Identity Politics: A Case Study of a Failed Human Relations Commission

2006· article· en· W2130442619 on OpenAlexaff
Judith Taylor

Bibliographic record

VenueSociological Perspectives · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSocial movementPoliticsSociologyIdentity (music)CommissionPolitical scienceHuman rights movementMulticulturalismMovement (music)Participant observationHuman rightsLawSocial scienceInternational human rights lawAesthetics

Abstract

fetched live from OpenAlex

This case study of the birth and death of a human relations commission in California contributes to our understanding of the emotional stakes of social movement participation and the meaning of multiculturalism in the U.S. post–civil rights era. The research indicates the extent to which resonant movement frames are necessary for movement success and how their absence can cause emotional harm to movement adherents. In this account of institutional activism, the frameworks of human relations and multiculturalism—simultaneously affective and amorphous— attracted participation but produced a harmful emotional climate and ultimately proved insufficient to inspire collective identity and action. Thus, instead of transforming social movement behavior, the state project of human relations deployed here succeeded in invigorating entrenched grievances and identities. Other factors, such as leadership, social movement identity work, and the “emotion culture” of movements are also discussed. Findings presented herein are based on one year of participant observation, twenty-four interviews, and analysis of public records.

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)0.008
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0570.023
Scholarly communication0.0100.005
Open science0.0030.008
Research integrity0.0090.010
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 head0.036
GPT teacher head0.368
Teacher spread0.332 · 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 designQualitative
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
Published2006
Admission routes1
Has abstractyes

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