Marginalized, Minimized and Forgotten: Gender Dynamics in Photojournalism, From a Global Sociohistorical Lens to the Local Case of Claire Beaugrand-Champagne in Quebec
Bibliographic record
Abstract
Claire Beaugrand-Champagne was 27 years-old when she completed her first assignment for Le Jour—a new, young, independentist and left-leaning daily newspaper in Montreal. The year was 1974, and she was by all historical accounts the first woman to photograph the news in Quebec. Relatively few women in the province have followed in her footsteps since. Globally, women continue to be vastly underrepresented among staff and freelance news photographers. This essay examines, from a sociohistorical angle, some of the gender-specific challenges women photojournalists face in newsrooms, as well as how they have been able to overcome or bypass the barriers to their integration. It draws from existing, but relatively thin research in the field of journalism, which tends to examine women news photographers in the context of the United States. As such, it attempts to make a contribution by extending focus around the emergence of women photographers in the sociopolitical context of Quebec, through the case study of Claire Beaugrand-Champagne.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.052 | 0.038 |
| Scholarly communication | 0.016 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".