Challenging Turbulent Times: Towards a Framework for Girl-Led Transnational Dialogues to Combat Sexual Violence
Bibliographic record
Abstract
Claudia Mitchell – PhD, James McGill Professor, McGill University, Montreal, Canada. Email: Claudia.mitchell@mcgill.ca Turbulent times in relation to sexual violence in the lives of girls and young women call for solidarity and global action. One of the effects of globalization is the increased recognition of a borderless world that, in some ways, erases the boundaries between 'over there' and 'over here', challenging some of the distinctions behind a Global North and a Global South. In this article, I offer an analysis of the issues behind sexual violence, which frame the possibilities for research teams working with girls and young women across the Global North and the Global South. At the same time, I highlight the possibilities for learning more about North-North and South-South interactions. What would such an approach entail and what kinds of strategies are useful for sustaining such a strategy in combating sexual violence? In particular, how can such a framework support dialogue? In order to address these questions the article suggests a practical framework which draws on the findings from a Canada-South Africa project, Networks for Change and in particular focuses on the importance of advocating for a public voice for girls and young women that is framed within an activist agenda. The article refers to this approach as a 'circles within circles' approach, arguing for both bringing together girls and young women who have been involved in participatory visual work from a number of country contexts, and ensuring that the circle puts girls and young women at the centre.
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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 | 0.050 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.034 | 0.102 |
| Scholarly communication | 0.041 | 0.032 |
| Open science | 0.007 | 0.030 |
| Research integrity | 0.013 | 0.016 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".