Generating Sociality through the Senses in Movement and Music Therapy among People with Recurrent Psychosis
Bibliographic record
Abstract
Psychosis analyzed from a phenomenological orientation is a disembodied experience that involves a constant negotiation of self and reality. For people experiencing recurrent psychoses, its medicalisation and stigmatisation further complicate the relationship of self, medication, and society, as shown by the political economy of psychosis. In these cases where full recovery from the illness may not be possible, I reconceptualise psychosis as a pastime: a strategy to coexist with rather than be defined by the illness experience. Accordingly, I turn towards non-pharmacological interventions; arts-based therapies, such as dance and music, have been shown to benefit people with psychosis by reestablishing their experience of reality within the body and empowering them to regain control over their lives and interpersonal relationships. In my ethnography of the Psychosis Therapy Project (PTP) based in Islington, London, UK, which serves people with recurrent psychoses, I explore how its movement and music therapies work towards re-embodiment using bodily techniques of heat, synchronicity, synesthesia, and the transportive role of music. Thus, I take a sensory anthropological approach to sociality that also decenters vision as the main sense in healing—to be well is to feel well rather than just to look well. Finally, my fieldwork presents a case where a service user, who regularly participates in the movement group, manages psychosis as a pastime through practical and social enskilment. Ultimately, my work strives to demedicalise and destigmatise the lived experience of psychosis and honour the legacy of the PTP.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.028 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".