Shared Sensorialities: Reshaping Cinema through Neurodiversity. A Conversation with Steven Eastwood on <i>The Stimming Pool</i> (2024)
Bibliographic record
Abstract
In this conversation, filmmaker and researcher Steven Eastwood reflects on the collaborative process behind the creation of The Stimming Pool (2024), co-directed with neurodivergent members of the Neurocultures Collective. He discusses the ethical and aesthetic stakes of a co-creation in which atypical subjectivities are not merely represented but actively participate in redefining the very codes of cinema. Reflecting on working methods grounded in slowness, trust, and attentiveness, Eastwood describes the development of an “autistic camera” and the exploration of non-linear narrative forms grounded in alternative perceptual regimes. Far from an illustrative or explanatory approach, the film embraces sensory and relational co-experimentation. In doing so, it offers a shift in perspective: a cinema shaped through alterity, resonance, and the shared inhabiting of divergent perceptual worlds.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.010 | 0.017 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".