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Record W3202206845

Reflection: Lived and Idealized Self and Other in Women’s Journals

2018· article· en· W3202206845 on OpenAlexaff
Nathalie Cooke, Jennifer Garland

Bibliographic record

VenueSSRN Electronic Journal · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsMcGill University
Fundersnot available
KeywordsForegroundingNegotiationPopularityContext (archaeology)Reading (process)Sociocultural evolutionSpace (punctuation)SociologyGender studiesReflection (computer programming)Media studiesPsychologyAdvertisingSocial psychologyPolitical scienceHistoryLinguisticsLiteratureSocial scienceArtComputer science
DOInot available

Abstract

fetched live from OpenAlex

Women’s magazines serve as sites of negotiation between prescriptive and descriptive practice – what women are told to do (in advertising, feature articles, and editorial copy, for example) and what they describe themselves as doing (in testimonials, interviews, columns, and letters to the editor). As such, they reinforce existing stereotypes of women’s roles through their editorials and advertising while also providing an outlet for women’s creative and life writing, opening avenues for lived and idealized selves and others. While this paradigm can account for the popularity of women’s magazines for both readers and advertisers, it fails to capture the dynamic and “contestatory” space that studies in this section of the book on “Gendered Space and Global Context” describe as constituting the genre. Consequently, we propose here a more nuanced paradigm, one foregrounding interplay and exchange of opinions – multidirectional rather than unidirectional – where the act of reading brings individual readers into contestatory negotiation with gender and body ideals, as well as with sociocultural norms from many parts of the world, not just China.

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)0.013
metaresearch head score (Gemma)0.017
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 score0.020
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0110.073
Scholarly communication0.0200.012
Open science0.0020.012
Research integrity0.0030.005
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 head0.029
GPT teacher head0.343
Teacher spread0.314 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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