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Record W1991091672 · doi:10.1177/1363461510378469

Raves, Psychosis, and Spirit Healing

2010· article· en· W1991091672 on OpenAlexaffabout
Mary V. Seeman

Bibliographic record

VenueTranscultural Psychiatry · 2010
Typearticle
Languageen
FieldPsychology
TopicHistorical Psychiatry and Medical Practices
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychosisPsychologyPsychoanalysisPsychotherapistPsychiatryArt

Abstract

fetched live from OpenAlex

This paper reflects the intersection of three cultures: the rave (all night dance party and use of the drug, Ecstasy) culture; the ward culture of an inpatient psychiatric program for First Episode Psychosis; the spirit healing culture of the Philippines. All three intersected in Toronto, Canada in the mid 1990s, as illustrated by the clinical case of a 19-year-old university student who was hospitalized with symptoms of drug-induced psychosis. Her initial treatment was not successful and presented dilemmas for the treating staff. Transfer to a second psychiatric facility that permitted attendance at a traditional Filipino healing ceremony resulted in a cure, with no recurrence 10 years later. According to James Dow's 1986 formulation, the components of the key spiritual healing session paralleled the very elements the young woman had sought by participating in raves, an activity that was problematic because it led to family displeasure. Whereas attendance at a rave triggered illness, the healing session, sanctioned by her family and taking place in their midst, resulted in healing.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.027
Scholarly communication0.0030.002
Open science0.0000.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.016
GPT teacher head0.326
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2010
Admission routes2
Has abstractyes

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