What are you (un)doing with that story?
Bibliographic record
Abstract
This paper contributes to growing inter-disciplinary discussion on what and how arts-informed community-engaged research can add to critical engagements with social inequalities. It is based on workshops facilitated by an inter-disciplinary university research group with the Women’s Housing Planning Collaborative Advisory in Hamilton, a funded housing project and self-advocacy group in a mid-sized Canadian city. In theoretically informed and carefully crafted exercises, workshop participants performed stories they felt compelled to tell in order to secure resources and empathy from social service professionals. These performances made visible the draining nature and practical limitations of interactions between clients and social service professionals in which only particular affective postures and stories of need qualify clients as worthy of concern. The women then used first-person narrative and image theatre to evoke the worlds they are imagining for themselves and others in their advocacy work. Drawing on feminist, post-colonial, anthropological, and performance studies literature, we describe and analyze how the workshops methods of dramatic ‘play’ enable nuanced, powerful, and collectively energizing critical engagements with painful norms of social (mis)recognition.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.015 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".