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Record W3204888445 · doi:10.21203/rs.3.rs-20519/v1

The Process of Injection Drug Use Among Homeless Women:A Qualitative Study

2020· preprint· en· W3204888445 on OpenAlexaff
Cynthia Kitson, Patrick O’Byrne

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsInjection drug useDrugQualitative researchProcess (computing)PsychologyMedicineSociologyComputer sciencePsychiatryDrug injectionSocial science

Abstract

fetched live from OpenAlex

Abstract Background: The literature on women who use injection drugs (WUID) is antiquated and diluted by data from men. Due to the higher rates of morbidity and mortality among WUID, we undertook a qualitative study to better understand their drug use practices. Methods: We adopted a Deleuzo-Guattarian lens and engaged in semi-structured interviews with 35 women. Data were analyzed applied thematic analysis. Results: We divided these themes into (1) how WUID obtain resources to acquire drug, and (2) the steps involved in preparing, using, and discarding drugs. From our Deleuzo-Guattarian perspective, these findings highlighted that participants stratified their worlds according to rules of cleanliness to create hierarchies of appropriateness and acceptability. Conclusions: These findings, overall, highlight the importance of understanding the constructed world of women who use injection drugs, particularly regarding the ways by which nurses interact with these women to provide care.

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)0.012
metaresearch head score (Gemma)0.015
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 score0.012
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.015
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0080.009
Scholarly communication0.0050.005
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.072
GPT teacher head0.411
Teacher spread0.339 · 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
Published2020
Admission routes1
Has abstractyes

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