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Record W2802084745 · doi:10.1177/1527476418768001

Broken Bodies/Inquiring Minds: Women in Contemporary Transnational TV Crime Drama

2018· article· en· W2802084745 on OpenAlexaff
Lisa Coulthard, Tanya Horeck, Barbara Klinger, Kathleen McHugh

Bibliographic record

VenueTelevision & New Media · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFeminismPopularityDramaCognitive reframingSociologyMedia studiesEmpowermentGender studiesAffect (linguistics)CredenceAestheticsPolitical sciencePsychologyVisual artsLawSocial psychologyArt

Abstract

fetched live from OpenAlex

This special issue concentrates on a dominant trend in contemporary transnational crime television: quality dramas featuring serial criminals who break the bodies/psyches of young women or children, thereby attracting the inquiries of female detectives who have suffered trauma themselves. This trend has generated resources, industrial partnerships, avid viewers, and, importantly for the authors here, feminist commentary across continents. We reframe the debate over whether these shows are feminist or misogynist by exploring staples of transnational language that underwrite their popularity in disparate national markets. In fact, we address the paradoxical gender-based violence and female empowerment at their core as crucial to their transnational legibility by tracking recurring elements that circulate a gendered and raced lingua franca rooted in fundamentals of media aesthetics: strategies of storytelling and genre, modes of perception, and the production of affect. Ultimately, these programs raise questions about cultural currencies of televised feminism in the digital era.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0110.015
Scholarly communication0.0110.007
Open science0.0010.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0100.001

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 head0.085
GPT teacher head0.338
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 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

Citations19
Published2018
Admission routes1
Has abstractyes

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