MétaCan
Menu
Back to cohort

Reflexivity: Interviewing Women and Men Formerly Addicted to Drugs and/or Alcohol

2014· article· en· W323653482 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Qualitative Report · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsReflexivityInterviewQualitative researchAddictionPower (physics)PsychologyField (mathematics)Semi-structured interviewSociologySocial psychologyPsychotherapistPsychiatrySocial science

Abstract

fetched live from OpenAlex

This article considers how one researcher used reflexivity in two research projects. Qualitative research often involves a consideration of sensitive topics, one which may include research with individuals formerly addicted to drugs and/or alcohol. However, there is little in the literature that focuses directly on such experiences for researchers in this field; that is, a consideration of how a researcher might use reflectivity while interviewing those formerly addicted to substances. Exploring the following themes, I highlight how I reflected on the experiences that my participants (25 women and 25 men) revealed about their stories of their addiction and recovery processes: (1) my personal characteristics and my background work; (2) the importance of documenting power balance or power imbalance in my research; (3) documenting the unexpected; and (4) reflecting on the impact of my interviews/field notes.

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.

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)0.039
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.302
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0390.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.741
GPT teacher head0.730
Teacher spread0.011 · 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