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Mothers talk about their children with schizophrenia: a performance autoethnography

2005· article· en· W2144709416 on OpenAlexaff
Barbara Schneider

Bibliographic record

VenueJournal of Psychiatric and Mental Health Nursing · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAutoethnographyEthnographySchizophrenia (object-oriented programming)PsychologySalientPsychoanalysisSociologyGender studiesPsychiatryAnthropologyHistory

Abstract

fetched live from OpenAlex

This article presents the script for a performance autoethnography that explores how mothers of adults with schizophrenia talk about their children. The script draws on my own experience as a mother of a person with schizophrenia, interviews I conducted with mothers of people with schizophrenia, and written accounts by mothers of people with schizophrenia. Autoethnography refers to an approach to social science research in which the experience of the researcher is recognized as a salient part of the research process. Autoethnography typically uses non-traditional genres, such as this script, for presenting research to address ethical and political problems in the representation of research. These genres allow researchers to both break with and continue the ethnographic tradition of representing the lives and experiences of others.

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)0.006
metaresearch head score (Gemma)0.008
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0060.006
Scholarly communication0.0030.002
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.118
GPT teacher head0.513
Teacher spread0.395 · 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

Citations23
Published2005
Admission routes1
Has abstractyes

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