Stretching Our Stories (SOS): Digital Worldmaking in Troubled Times
Bibliographic record
Abstract
In this article, we reflect on the pivot to online research creation in COVID’s wake, and offer a gallery of ten films that emerged through on-line multimedia story-making under lockdown conditions. We describe what new, online research creation has meant for us as critical disability and intersectionality scholars who work with creative visual methods—both with and in justice-seeking communities. We introduce COVID-era adaptions to the research creation practices we co-developed that helped to sustain racialized/allied, disability, fat, neurodivergent, mad, aging cultures and communities during the pandemic. We focus on the bifurcated affective economies that circulated around COVID, and how these affects surface in the stories of makers who participated in on-line multimedia workshops that we have run since March 2020. While the pandemic has deepened inequalities and disrupted research and arts activism, we argue that it provided opportunity to expand possibilities for disability and non-normative cultural production and to imagine and fight for a radically different world.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.023 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 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".