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Record W2096219899 · doi:10.1177/0010414004263662

Explaining Social Movement Outcomes

2004· article· en· W2096219899 on OpenAlexaff
Susan Franceschet

Bibliographic record

VenueComparative Political Studies · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical and Social Dynamics in Chile and Latin America
Canadian institutionsAcadia University
Fundersnot available
KeywordsPoliticsContext (archaeology)Political opportunityGender studiesSocial movementMeaning (existential)FeminismSociologyCollective actionPolitical scienceMovement (music)Frame (networking)Political economyLawPsychology

Abstract

fetched live from OpenAlex

This article compares the outcomes of first- and second-wave feminism in Chile. The author argues that the double-militancy strategy of second-wave feminists emerged out of shifts in the political opportunity structure that led the movement to adapt its collective action frame. First-wave feminists had constructed a gender frame that depicted women as apolitical. In a context in which political parties were class based and saw little need to address women’s issues, neither the gender frame nor the political opportunity structure invited a double-militancy strategy. The context for second-wave activists was different. The politicization of women’s maternal identities altered the meaning of the maternal gender frame. Because the prodemocracy parties needed the support of women’s movements (and female voters), they invited women’s participation. Thus, the political opportunity structure and a more politicized gender frame encouraged a double-militancy strategy, ultimately leading to the realization of some of the movement’s goals.

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)0.004
metaresearch head score (Gemma)0.012
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0030.005
Scholarly communication0.0040.004
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0400.001

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 head0.188
GPT teacher head0.469
Teacher spread0.281 · 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

Citations50
Published2004
Admission routes1
Has abstractyes

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