Bibliographic record
Abstract
Although more women than ever work in Canadian media, their participation in journalism seems misunderstood or underexplored. That was the message emerging from Women in the Field, a symposium hosted by the Ryerson Journalism Research Centre in2011. More than 200 journalists and journalism students gathered to discuss dilemmas facing women–from covering high-risk events to balancing parenthood with careers. Participants discussed equality in newsrooms, asking whether women are fairly represented and whether they cover news differently from men. This narrative literature review reports on what scholars know about the state of women in Canadian news by identifying common lines of inquiry, comparing conflicting findings, teasing out ambiguities arising from multidisciplinary approaches, and pointing to areas requiring further research. Describe your data as well as you can. Formatting is preserved when pasting from other sources and counts towards character limits.
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 | 0.012 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.014 | 0.017 |
| Scholarly communication | 0.019 | 0.023 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".