“We cannot win this fight if we don’t acknowledge any such fight exists”: Examining media coverage of Black women’s risk for intimate partner violence
Bibliographic record
Abstract
Research and policy continue to focus on the prevalence of intimate partner violence (IPV) in the U.S., with estimates indicating that 81 million people have been victimized by a partner in their lifetime. IPV disproportionately impacts women, and Black women in particular face victimization at a much higher rate when compared to other groups. Considering their overrepresentation, advocates have called for increased attention to IPV and its associated risks for Black women. As one of the most effective ways to publicize important health-related information is through the media, assessing coverage and framing is essential to understanding whether risks and resources are successfully communicated. The current study analyzes media attention to Black women’s elevated risk of victimization, and finds that while coverage is relatively minimal, media sources employ framing devices such as statistics, expert commentary, and single-victim focal points to discuss the issue. Three prominent themes emerged in content analysis of the media coverage, as news article language served to promote risk awareness, provide risk explanation, and/or address risk criticism.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".