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Record W2765364676 · doi:10.1177/1049732317731539

Prehending Addiction: Alcohol and Other Drug Professionals’ Encounters With “New” Addictions

2017· article· en· W2765364676 on OpenAlexaboutno aff
Adrian Farrugia, Suzanne Fraser

Bibliographic record

VenueQualitative Health Research · 2017
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsnot available
FundersAustralian Research CouncilStockholms UniversitetCurtin University of TechnologyNational Drug Research InstituteAustralian Government
KeywordsAddictionSubjectivityHealth professionalsPsychologyQualitative researchSociologyPsychiatryHealth carePolitical scienceEpistemologySocial scienceLaw

Abstract

fetched live from OpenAlex

This article investigates the ways new forms of addiction are encountered by professionals working in the area of alcohol and other drugs. Combining interviews with policymakers, service providers, and peer advocates in three countries (Australia, Canada, and Sweden), and Mike Michael's utilization of the notion of prehension for science communication, we track the notions of addiction, drugs, and subjectivity that emerge when alcohol and other drug professionals encounter what Fraser, Moore and Keane call the addicting of nonsubstance-related practices. The analysis has three parts: constituting addiction unity, questioning addiction unity, and conflicting logics of addicting processes. We argue that specific articulations of drugs and health and specific health professional and addiction subjects are made anew in these encounters. These notions of drugs, health, and subjectivity shape how alcohol and other drug professionals engage with substance-related addictions. In concluding, we consider the implications of new addictions for professional practice.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.411
GPT teacher head0.589
Teacher spread0.178 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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