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Record W2898958987 · doi:10.22215/etd/2018-13267

"A Disconnect Between What She Wanted To Do And Her Ability To Act Upon It": Complexities Of Agency In Discourses Of Treatment For Youth With Eating Disorders

2018· dissertation· en· W2898958987 on OpenAlexaffabout
April-Rose Krause

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMedicine
TopicEthics and Legal Issues in Pediatric Healthcare
Canadian institutionsCarleton University
Fundersnot available
KeywordsNarrativeGlobePoliticsAgency (philosophy)Opposition (politics)NewspaperGender studiesContext (archaeology)Media studiesEating disordersSociologyPolitical sciencePsychologySocial scienceLawPsychiatryHistoryLiteratureArt

Abstract

fetched live from OpenAlex

This project analyzes the discourses circulating about young people with eating disorders (ED) in popular and legal materials.Through use of discourse analysis through a Foucauldian lens, I have determined major themes in how we make sense of involuntary treatment, in particular.In analyzing cases from the Ontario Consent and Capacity Board (CCB) and newspaper articles from The Globe and Mail, Toronto Star, Ottawa Citizen, Ottawa Sun, and National Post I drew out common narratives and themes.Agency, not surprisingly in the current medico-political context was noted throughout all texts, and was found to be alongside or in opposition to, discourses of protection.I drew out three themes which framed this overarching tension: (1) hospitalization experiences: outcome oriented approaches to treatment; (2) the family unit: a source of harm and care; and (3) the patient as a broken child.Legislative documents and regulatory frameworks were used to provide the backdrop upon which this discourse plays out.Youth with EDs are the bodies upon which these discourses are written, producing them as particular kinds of subjects.My analysis reveals that there remain fundamental tensions in how we understand the young person with an eating disorder and how they should be treated.Any progressive changes to legislation or health care frameworks must address these tensions around youth agency or they will merely reproduce the current issues.

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)0.019
metaresearch head score (Gemma)0.024
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 score0.079
Threshold uncertainty score0.195

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0260.078
Scholarly communication0.0140.012
Open science0.0020.010
Research integrity0.0050.008
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 head0.071
GPT teacher head0.414
Teacher spread0.343 · 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

Citations0
Published2018
Admission routes2
Has abstractyes

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