Multimedia Storytelling Methodology: Notes on Access and Inclusion in Neoliberal Times
Bibliographic record
Abstract
In this article, the authors examine the impact of using their evolving multimedia storytelling method (digital art and video) to challenge dominant representations of non-normative bodies and foster more inclusive spaces. Drawing on their collaborative work with disability and non-normatively embodied artists and communities, they investigate the challenges of negotiating what ‘access’ and ‘inclusion’ mean beyond the individualizing discourses of neoliberalism without erasing the specificities of differentially-lived experiences. Reflecting on their experiences in a variety of workshops and on a selection of videos made in those workshops, they identify and analyze three iterative ‘movements’ that mark their storytelling processes: from failure to vulnerability, from time to temporality, and from individual voice to collective concerns. The authors end by considering some of the ways they have experimented with developing an iterative workshop method that welcomes difference while simultaneously allowing for an examination of the terms of the shared space and of the mechanisms of inclusion and exclusion operating within that space.
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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 | 0.026 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.013 | 0.038 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".