What is sex journalism or, rather, how does it become? Interviews with news workers on the risk and precarity of a gendered news niche
Bibliographic record
Abstract
Numerous studies have found the reporting of sex is sensationalized and intended to create controversy while journalists have little regard for the topic. Such matters are important given the #MeToo movement has broadened public debate about sexual issues, practices and behaviors. However, there is scant research on the professional identities of journalists who specialize in sex news and the industrial, social and individual-level factors shaping their reportage. Extending an earlier qualitative study comprising interviews with female freelance journalists in North America, Canada, Germany and Australia, this article conceptualizes sex journalism as a specialism in flux and, using the concept of ‘biodigital vulnerability’, argues that sex journalists are exposed to gendered experiences of risk in their news work. The results suggest greater consideration for the professional and gendered identities of sex journalists may improve sex news coverage and optimize sexual health outcomes given the importance of sex news as a public information source.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.015 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| 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 source (direct Gemma or distilled Codex), 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".