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Record W2766591379 · doi:10.1080/0966369x.2017.1387105

Building the City of Women: creating a site of feminist resistance in a northern Colombian conflict zone

2017· article· en· W2766591379 on OpenAlexfundno aff
Julia Zulver

Bibliographic record

VenueGender Place & Culture · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicConflict, Peace, and Violence in Colombia
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaCommonwealth Scholarship Commission
KeywordsResistance (ecology)FeminismGender studiesFace (sociological concept)OddsLeagueVariety (cybernetics)SociologyPolitical scienceSocial science

Abstract

fetched live from OpenAlex

Against all odds, in uncertain and violent times, Colombian women are mobilising for peace. They do so even when they face ongoing violence and personal threats from a variety of armed actors. Despite a well-established tradition of studying women’s social movements in times of conflict, there is a lacuna when it comes to analysing feminism as a mobilisation strategy. This article uses the case study of the League of Displaced Women, the Liga de Mujeres Desplazadas (LMD) to illustrate the utility of Zulver’s High Risk Feminism framework to explain how and why women chose to build the City of Women, despite the real and threatened danger that this implied. The article narrates the history of the LMD, from its foundations in a geography of marginality to its creation of a space of resistance for displaced women and their families. In all, this articles demonstrates how feminist resistance has not only become a way of life for the women of the LMD, but also a strategy for creating pockets of safe places in the midst of a conflict zone.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.587
Threshold uncertainty score0.910

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.332
Teacher spread0.290 · 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.

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

Citations12
Published2017
Admission routes1
Has abstractyes

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