Personal stories, public voices: Performance for public-making
Bibliographic record
Abstract
The project described in this paper rests on a belief in the power and significance of storytelling in social change processes. It also takes seriously worries and critique about ‘what happens’ when personal stories of troubles or suffering are told to strangers, particularly as they revolve around contradictory claims about empathy. Over several months our research team worked with a group of women who have experienced homelessness and who are advocates for themselves and other women in our community. The women participated in a series of storytelling and image theatre workshops and exercises that formed the basis of a 20-minute dramatic vignette centered on their interactions with social services in the city. The creative process was designed to value the knowledge carried in personal stories of lived experience, while harnessing the power of the arts to evade some of the problematics of personal storytelling in public spaces. The women performed the vignette for social work students. In this paper we reflect on comments from students who witnessed the performance and offer our analysis of their responses in relation to specific features of the drama. In a discursive context that holds individuals responsible for all manner of social problems, we consider the potential of projects like this one for summoning and mobilizing publics and publicness.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.028 | 0.043 |
| Scholarly communication | 0.028 | 0.021 |
| Open science | 0.003 | 0.030 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".