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Record W3188670043 · doi:10.1017/lap.2021.24

On the Strategic Uses of Women’s Rights: Backlash, Rights-based Framing, and Anti-Gender Campaigns in Colombia’s 2016 Peace Agreement

2021· article· en· W3188670043 on OpenAlexaff
Elizabeth S. Corredor

Bibliographic record

VenueLatin American Politics and Society · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsBacklashFraming (construction)Opposition (politics)Human rightsNormativePoliticsSociologyGender studiesRhetoricSocial movementPolitical scienceFeminismFeminist movementLaw

Abstract

fetched live from OpenAlex

ABSTRACT This article examines organized opposition to feminist and LGBTI political projects in Colombia. Although there is a large body of literature on feminist movements and a growing literature on LGBTI movements, there is little research on resistance to them. Through an intersectional feminist lens, this study analyzes the “anti-gender” campaign organized against the gender perspective in Colombia’s 2016 peace agreement to demonstrate the limitations of backlash theory and certain normative understandings of human rights. In contrast to assumptions that backlash is predetermined, the study demonstrates that the anti-gender mobilization against the peace agreement was circumstantial rather than inevitable. To highlight the productive nature of backlash, it traces how opponents employed human rights rhetoric to establish an alternative present and promote an imagined future rooted in exclusion and repression. In addition, it shows that mobilized backlash against feminist and LGBTI movements does not necessarily decelerate or reverse the respective movements’ agendas.

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)0.005
metaresearch head score (Gemma)0.007
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 score0.029
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0090.015
Scholarly communication0.0090.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.032
GPT teacher head0.291
Teacher spread0.259 · 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

Citations72
Published2021
Admission routes1
Has abstractyes

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