MétaCan
Menu
Back to cohort
Record W2476130368 · doi:10.1057/9780230607019_13

Girl Culture and Digital Technology in the Age of AIDS

2007· book-chapter· en· W2476130368 on OpenAlexaff
Claudia Mitchell, Jacqueline Reid‐Walsh

Bibliographic record

VenuePalgrave Macmillan US eBooks · 2007
Typebook-chapter
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsConcordia University
Fundersnot available
KeywordsInscribed figureGirlReading (process)FemininityHuman sexualitySubject matterSemioticsRomanceGender studiesSubject (documents)ArtSociologyMedia studiesLiteraturePsychologyPolitical scienceDevelopmental psychology

Abstract

fetched live from OpenAlex

In this chapter we focus on girls’ magazine reading, examining both traditional hard copy and digital versions of popular magazines targeting girls. We investigate how magazines represent issues around female bodies and sexuality and how girls, through the process of reading traditional and digital texts, participate in the information culture that surrounds them. As Angela McRobbie (1999) observes in her essay on girls’ magazines: “For over twenty years feminists have singled out girls’ magazines and women’s magazines as commercial sites of intensified femininity and hence rich fields of analysis and critique” (p. 46). Research on magazines aimed at the young teen market, like the work done on women’s magazines more generally, has been extensive. Investigations into this subject range from McRobbie’s work in the 1980s and early 1990s, where she offered a semiotic reading on the codes of romance found in these magazines, to Dawn Currie’s straightforward content analysis of these texts and their readers. Currie’s work (1999) and additional research demonstrate that readers of teen magazines are mainly young teens and preteens, no matter the inscribed textual age of the magazine (such as Seventeen).

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.817
Threshold uncertainty score0.697

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.021
GPT teacher head0.268
Teacher spread0.247 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations1
Published2007
Admission routes1
Has abstractyes

Explore more

Same venuePalgrave Macmillan US eBooksSame topicDigital Games and MediaFrench-language works237,207