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Record W4220699081 · doi:10.1093/socpro/spac020

Women Who Break the Glass Ceiling Get a “Paper Cut”: Gender, Fame, and Media Sentiment

2022· article· en· W4220699081 on OpenAlex

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

VenueSocial Problems · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsMcGill University
Fundersnot available
KeywordsScrutinyNewspaperMedia coverageGlass ceilingSocial mediaRank (graph theory)Scale (ratio)PsychologyAdvertisingSociologyMedia studiesPolitical scienceLawGeographyMathematicsBusiness

Abstract

fetched live from OpenAlex

Abstract Past quantitative studies have shown that most media coverage is of men. Here we ask if the scarce coverage that women get is qualitatively different from that of men. We use computer-coded sentiment scores for 14 million person names covered in 1,323 newspapers to investigate the three-way relationship between gender, fame, and sentiment. Additional large-scale data on occupational categories allow us to compare women and men within the same profession and rank. We propose that as women’s fame increases their media coverage becomes negative more quickly when compared to men (a “paper cut”), because their violation of gender hierarchies and social expectations about typical feminine behavior evokes disproportionate scrutiny. We find that while overall media coverage is much more positive for women than for men, this difference disappears and even reverses at higher levels of fame. In encyclopedic sentiment data we find no biographic basis for women’s disproportionate decline in media coverage sentiment at high fame, consistent with the conjectured double standard in media discourse.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.386
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
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 head0.041
GPT teacher head0.295
Teacher spread0.254 · 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