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Record W1564175401 · doi:10.1111/anti.12092

“This is how I want to live my life”: An Experiment in Prefigurative Feminist Organizing for a More Equitable and Inclusive City

2014· article· en· W1564175401 on OpenAlexafffund
Janet Siltanen, Fran Klodawsky, Caroline Andrew

Bibliographic record

VenueAntipode · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsUniversity of OttawaInstitute on GovernanceCarleton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGrassrootsCredibilityState (computer science)Community organizingPoliticsSociologyPerspective (graphical)Diversity (politics)Public relationsWork (physics)Public administrationPolitical scienceLawEngineeringComputer science

Abstract

fetched live from OpenAlex

Abstract This paper aims to think differently about possibilities for feminist organizing in cities. We use a current experiment with city‐based feminist organizing to explore how it can be possible to work with the local state while at the same time challenging and disrupting understandings and practices that marginalize the diversity of women's needs, contributions and concerns. Trying to work “inside” the local state while maintaining an “outside” critical perspective involves a tricky balancing act between being inside enough to have credibility and effectiveness within the business of city politics and administration, and outside enough to maintain strong connections with the community and grassroots support. In managing this balancing act, we argue that the organization enacts a strategic use of prefiguration both within the organization and when engaging the local state.

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)0.022
metaresearch head score (Gemma)0.016
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 score0.022
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0190.019
Scholarly communication0.0060.005
Open science0.0030.007
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0140.001

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 head0.035
GPT teacher head0.334
Teacher spread0.299 · 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

Citations56
Published2014
Admission routes2
Has abstractyes

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