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Record W4282044630 · doi:10.1177/14614448221096806

Opening up mediation opportunities by engaging grassroots data: Adaptive and resilient feminist data activism in China

2022· article· en· W4282044630 on OpenAlexaff
Yu Sun, Siyuan Yin

Bibliographic record

VenueNew Media & Society · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGrassrootsMediationTransformative mediationContentious politicsAuthoritarianismSociologyChinaContext (archaeology)MainstreamPolitical opportunityPoliticsPolitical scienceSocial movementPublic relationsDemocracySocial scienceAlternative dispute resolutionLaw

Abstract

fetched live from OpenAlex

This article explores the dynamics and practices of feminist data activism that engages with grassroots data to archive cases of sexual violence in China. Drawing on Cammaert’s notion of the mediation opportunity structure, we investigate the mediation process of a feminist data campaign and activists’ communicative practices in contemporary China. By practicing data-activist research, our study shows that the data-based action repertoire opens up hybrid and contingent mediation opportunities for an anti-sexual violence campaign under the current political opportunity structure. We find the paradox of seeking visibility while refusing mainstream media coverage in activist tactics, which embodies a form of adaptive and resilient feminist data activism in the authoritarian context of China. This case study suggests that the dynamics of feminist data activism in China are configured by the tripartite interaction among the disruptive action repertoire, mediation opportunity structure, and political conditions.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.122
GPT teacher head0.339
Teacher spread0.217 · 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.

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

Citations16
Published2022
Admission routes1
Has abstractyes

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