Telling stories without the words: ‘Tightrope talk’ in women’s accounts of coming to live well after rape or depression
Bibliographic record
Abstract
Narratives and language available within a cultural context reflect and reify power structures that are reproduced in everyday social interactions. In this article, we explore the narrative challenges and possibilities that emerged in our respective research programmes with women who have faced depression or rape. These experiences are, at least in part, products of patriarchy and are regulated by hegemonic discourses that individualize and depoliticize women’s experiences. In our studies, we faced significant challenges of conducting research when dominant narratives fail the storytellers, and came to understand these as products of what Marjorie DeVault has termed ‘linguistic incongruence’. We examine women’s attempts to negotiate the telling of their stories without adequate language and framings, and our attempts to listen carefully to the emergence of counterstories. We introduce the notion of ‘tightrope talk’ to refer to participants’ attempts to make meaning of their experiences, as they negotiate both agency and blame in ways that dominant narratives fail to do. We conclude by discussing the potential dangers of these efforts.
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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 | 0.014 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.018 | 0.046 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.002 | 0.013 |
| 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".