MétaCan
Menu
Back to cohort
Record W2901704990 · doi:10.1177/2333393618810655

“ <i>A Two Glass of Wine Shift</i> ”: Dominant Discourses and the Social Organization of Nurses’ Substance Use

2018· article· en· W2901704990 on OpenAlexaff
Charlotte A. Ross, Sonya L. Jakubec, Nicole S. Berry, Victoria Smye

Bibliographic record

VenueGlobal Qualitative Nursing Research · 2018
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsWestern UniversityMount Royal UniversitySimon Fraser UniversityDouglas College
Fundersnot available
KeywordsWineSubstance usePsychologySociologySocial psychologyPsychoanalysisPsychiatryFood scienceChemistry

Abstract

fetched live from OpenAlex

We undertook an institutional ethnography utilizing the expert knowledge of nurses who have experienced substance-use problems to discover: (a) What are the discourses embedded in the talk among nurses in their everyday work worlds that socially organize their substance-use practices and (b) how do those discourses manage these activities? Data collection included interviews, researcher reflexivity, and texts that were critically analyzed with a focus on institutional features. Analysis revealed dominant moralistic and individuated discourses in nurses' workplace talk that socially organized their substance-use practices, subordinated and silenced experiences of work stress, and erased employers' roles in managing working conditions. Conclusions included that nurses used substances in ways that enabled them to remain silent and keep working. Nurses' education did not prepare them regarding nurses' substance-use problems or managing emotional labor. Nurses viewed alcohol as an acceptable and encouraged coping strategy for nurses to manage emotional distress.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.008
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 head0.123
GPT teacher head0.528
Teacher spread0.405 · 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 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

Citations29
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueGlobal Qualitative Nursing ResearchSame topicHIV, Drug Use, Sexual RiskFrench-language works237,207