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Record W2530449463 · doi:10.1080/09589236.2016.1243044

Tangles, tears and messy conversations: using a media discussion group to explore notions of strong women

2016· article· en· W2530449463 on OpenAlex
Laura Lane, Vera Woloshyn, Nancy Taber

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Gender Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsBrock University
Fundersnot available
KeywordsTearsGroup (periodic table)PsychologyGender studiesSociologyMedicinePhysicsSurgery

Abstract

fetched live from OpenAlex

In this article, we discuss the experiences of six female secondary-school students participating in a media group that encouraged critical discussion and analysis of gender, particularly with respect to notions of strong women in popular media texts. Throughout the study, the participants viewed various forms of media and critically discussed gender representations. We describe the ways that we encouraged critical discussion that prompted the participants to challenge dominant perspectives and develop personal positions regarding gendered representations in popular media. Many discussions were convoluted and often contradictory. Throughout these debates, however, moments emerged in which participants identified complexities associated with gendered representations of strong women as related to privilege, beauty ideals and autonomy. We identify these moments as messy yet critical, requiring the researchers to challenge participants’ postfeminist notions of strong women. We emphasize the importance of ongoing dialogue and the potential of media for encouraging discussion.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.008
Threshold uncertainty score0.193

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.220
GPT teacher head0.389
Teacher spread0.169 · 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