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Record W3160330707

Platform Feminism: Feminist Protest Space and the Politics of Spatial Organization

2020· dissertation· W3160330707 on OpenAlexaffabout
Rianka Singh

Bibliographic record

VenueTSpace · 2020
Typedissertation
Language
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFeminismPoliticsSpace (punctuation)Gender studiesPolitical scienceSociologyComputer scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

Platform Feminism: Feminist Protest Space and the Politics of Spatial Organization examines the relationship between platforms and feminist politics. This dissertation proposes a new feminist media theory of the platform that positions the platform as a media object that elevates and amplifies some voices over others and renders marginal resistance tactics illegible. This dissertation develops the term “Platform Feminism” to describe an emerging view of digital platforms as always-already politically useful media for feminist empowerment. I argue that Platform Feminism has come to structure and dominate popular imaginaries of what a feminist politics is. In the same vein, the contemporary focus on digital platforms within media studies negates attention to the strategies of care, safety and survival that feminists who resist on the margins employ in the digital age. If we take seriously the imperative to survive rather than an overbearing commitment to speak up, then the platform’s role in feminism is revealed as limited in scope and potential. Through a mixed methodological approach via interviews with feminist activists, critical discourse analysis of platform protest materials, critical discourse analysis of news coverage and popular cultural responses to transnational feminist protests and participant observation within sites of feminist protest in Toronto, this dissertation argues that the platform is a media object that is over-determined in its political utility for Feminist politics and action.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.711
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.277
Teacher spread0.253 · 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

Citations2
Published2020
Admission routes2
Has abstractyes

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