Tangles, tears and messy conversations: using a media discussion group to explore notions of strong women
Bibliographic record
Abstract
In this article, we discuss the experiences of six female secondary-school students participating in a media group that encouraged critical discussion and analysis of gender, particularly with respect to notions of strong women in popular media texts. Throughout the study, the participants viewed various forms of media and critically discussed gender representations. We describe the ways that we encouraged critical discussion that prompted the participants to challenge dominant perspectives and develop personal positions regarding gendered representations in popular media. Many discussions were convoluted and often contradictory. Throughout these debates, however, moments emerged in which participants identified complexities associated with gendered representations of strong women as related to privilege, beauty ideals and autonomy. We identify these moments as messy yet critical, requiring the researchers to challenge participants’ postfeminist notions of strong women. We emphasize the importance of ongoing dialogue and the potential of media for encouraging discussion.
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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 | 0.019 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.025 | 0.018 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".