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Record W4303184158 · doi:10.22329/csw.v23i1.7589

Resisting Recovery Rhetoric: A Critical Discourse Analysis and Counter Perspectives from People With Substance Use Issues in Rural Ontario

2022· article· en· W4303184158 on OpenAlexaffvenueabout
Sandra McNeil

Bibliographic record

VenueCritical Social Work · 2022
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOppressionRhetoricSociologySubstance useDominance (genetics)Gender studiesQualitative researchPublic relationsSocial psychologyCriminologyPsychologyPolitical scienceSocial sciencePoliticsLaw

Abstract

fetched live from OpenAlex

The recovery concept informs research, policies, and practices related to mental health and substance use in Canada, which has consequences for people with substance use issues in rural areas. Although recovery is espoused as a personal journey with no “right” approach, dominant representations of recovery permeate public and private minds to (re)produce an ideal presumably urban-centered recovery, which may stigmatize people in rural communities. This qualitative, exploratory study draws on Foucauldian and intersectionality principles to examine power relations embedded in recovery discourse. A critical discourse analysis (CDA) using van Dijk’s Sociocognitive Approach (SCA) is applied to 40 semi-structured interviews with people who experience substance use issues in rural Ontario. Findings indicate that although dominant assumptions of substance use recovery are reinforced by people with lived experience in rural spaces, they are also rejected and resisted in ways that expose oppression, counter dominance, and promote more equitable alternatives.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.100
GPT teacher head0.420
Teacher spread0.321 · 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 teacher head, not a consensus.

Study designObservational
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
Published2022
Admission routes3
Has abstractyes

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