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Record W3156003087 · doi:10.28968/cftt.v7i1.34101

Digital Self-Monitoring, Bodied Realities: Re-Casting App-Based Technologies in First Episode Psychosis

2021· article· en· W3156003087 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCatalyst Feminism Theory Technoscience · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicMental Health and Psychiatry
Canadian institutionsCentre for Addiction and Mental HealthUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsScholarshipMaterialismEnthusiasmField (mathematics)SociologyPsychosisEmerging technologiesPsychologyEpistemologyPolitical sciencePsychiatrySocial psychologyComputer scienceLaw

Abstract

fetched live from OpenAlex

Smartphone technology has seen expanding interest across nearly all areas of medicine, including psychiatry. This paper discusses the burgeoning use of digital technologies for symptom monitoring in the field of first episode psychosis. Drawing on Foucauldian theory as well as intersectional feminist materialist and critical disabilities scholarship in science and technology studies (STS), we trace a novel landscape of technologies of the self. We explore the discursive strategies that position first episode psychosis and digital technology as progressive, curative paradigms and utilize our own ethnographic work within the field of first episode psychosis to consider how lived experience is transformed within and through digital technologies. We trouble the unfettered enthusiasm for digital technologies in first episode psychosis in light of how these transformations can be understood within a larger neoliberal political rationality and demarcate the importance of having intersectional feminist STS scholarship attend to this burgeoning field.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.769
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.271
Teacher spread0.242 · 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