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Record W6921398552 · doi:10.7910/dvn/5ajmsl

Replication Data for: Dimensions of Transnational Feminism: Autonomous Organizing, Multilateralism and Agenda-Setting in Global Civil Society

2024· dataset· en· W6921398552 on OpenAlexaff

Bibliographic record

VenueHarvard Dataverse · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCivil societyGrassrootsMultilateralismAutonomySocial movementReplication (statistics)Empirical researchFeminism

Abstract

fetched live from OpenAlex

The importance and impact of feminist mobilization across borders is well documented, but the impact of autonomy as an aspect of such organizing has not been explored in the transnational context. We argue that to understand the impact of transnational feminist mobilization, at least two distinct types of feminist mobilization require further conceptual development and empirical exploration in the transnational context, namely, autonomous as contrasted with multilateral mobilization. We offer a conceptual framework for distinguishing and studying these two forms. Further, using a mixed-methods study design, we empirically distinguish domestic and transnational dimensions of feminist activism and illuminate the impact of both multilateral feminist organizing and autonomous feminist organizing in the transnational space. Our analysis reveals that domestic and transnational organizing are distinct but related phenomena. We also find that in online organizing spaces, autonomous feminist campaigns amplify the messaging of geographically dispersed grassroots and individual activists more than multilateral ones. It further suggests that autonomous movements may offer more potential for representing marginalized groups of women, though this potential may not always be realized. The paper offers new concepts and empirical insights for the study of transnational feminism, thereby enabling a new research agenda. Further, this research contributes to the study of the ways that Transnational Social Movements can enrich global civil society and deepen global democracy.

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)0.003
metaresearch head score (Gemma)0.024
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.166
Threshold uncertainty score0.554

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.024
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.010
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.1660.096

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 head0.039
GPT teacher head0.312
Teacher spread0.273 · 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
GenreDataset

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

Citations1
Published2024
Admission routes1
Has abstractyes

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