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Record W2099956935 · doi:10.1177/1081180x05279147

Women and Crisis Reporting

2005· article· en· W2099956935 on OpenAlexaff
John B. Sutcliffe, Martha F. Lee, Walter C. Soderlund

Bibliographic record

VenueHarvard International Journal of Press/Politics · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsConsistency (knowledge bases)Representation (politics)Content analysisMedia coveragePoliticsAffect (linguistics)News mediaPolitical scienceAdvertisingHistoryPublic relationsPsychologyMedia studiesSociologyLawSocial scienceBusinessComputer science

Abstract

fetched live from OpenAlex

This article examines U.S. network television news coverage of seven political/military crises occurring in the Caribbean Basin. It first documents the extent to which women are involved in covering these crises. In line with existing research, women are found to be underrepresented in all major aspects of on-air media coverage. The article then explores the impact of this under representation on the actual content of media reporting. There is, at the very least, a possibility that those doing the reporting affect the content of the report, as well as who is chosen as a news source, either on-camera and/or quoted. The article examines this question using the technique of “paired comparisons”;specifically, it compares news stories dealing with four of the crises filed from the same location, on the same day, by male and female reporters representing at least two networks. The major finding of this research is that while there are subtle differences in the way in which male and female reporters frame stories, there is a broad consistency in male and female reporting. It is the case, however, that female anchors and reporters are slightly more likely to use female sources in their stories.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.891
Threshold uncertainty score0.236

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 head0.055
GPT teacher head0.360
Teacher spread0.305 · 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 designNot applicable
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

Citations14
Published2005
Admission routes1
Has abstractyes

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