Narrating the Field of Communication Through Some Female Voices: Women’s Experiences and Stories in Academia
Bibliographic record
Abstract
Abstract The field of communication has been constructed through primarily masculinized stories, such as the myth of the “founding fathers,” a situation that has tended to exclude the views and figures of female researchers. This article tries to remedy this by recovering the voices of women via eight in-depth interviews among prominent researchers (second-generation, 1960s–1970s) from Australia, Brazil, Canada, France, Italy, the UK, and the US. The results illustrate the inequality, sexual harassment, lack of legitimacy, and stereotypes faced by these women, and their strong emotional leadership. Their stories of success show how academia is a field of struggle where hegemony, domination, and resistance coexist. However, female experiences in academia are diverse and complex. That is why the article concludes with the need to continue tracking the stories of so many different women as knowing subjects, as well as the challenges of intersectionality in the epistemological construction of the field.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.019 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".