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Record W7054407415

‘Accidental Celebrities’: Magazine Coverage of Women Involved in U.S. Presidential Scandals

2023· article· en· W7054407415 on OpenAlexaff

Bibliographic record

VenueUniversity of Zagreb University Computing Centre (SRCE) · 2023
Typearticle
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsÉcole Nationale d'Administration PubliqueUniversité de Sherbrooke
Fundersnot available
KeywordsPresidential systemGovernment (linguistics)HeadlineNewspaperAgency (philosophy)News mediaRepresentation (politics)
DOInot available

Abstract

fetched live from OpenAlex

Using quantitative analysis, we analyzed the coverage of women indirectly involved in four major U.S. presidential scandals (Watergate, Iran-Contra, Clinton-Lewinsky affair, Ukraine quid pro quo) through 258 articles published in six magazines (The Atlantic, The New York Times Magazine, Time, The New Yorker, Newsweek, Rolling Stone) to assess how they are described by journalists.Three assumptions guided our analysis.First, women are covered in a negative way even if they are not responsible for the scandal.Second, they are covered by the magazines in a stereotypical way to describe their behavior, their character, or their role in the scandal.Finally, the coverage of women involved in more recent scandals is less stereotypical and less negative.While the literature shows that women receive more negative coverage than men when they are responsible for political scandals, our results show that this is also the case for these "accidental celebrities".

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)0.001
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0210.004

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 head0.005
GPT teacher head0.163
Teacher spread0.158 · 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
Published2023
Admission routes1
Has abstractno

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