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Record W2162367953 · doi:10.1177/1525822x03015002004

Active Interview Tactics in Research on Public Deviants: Exploring the Two-Cop Personas

2003· article· en· W2162367953 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

VenueField Methods · 2003
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsMemorial University of NewfoundlandMcMaster University
Fundersnot available
KeywordsDeviance (statistics)SociologyPersonaNarrativeSituatedSocial psychologyPublic relationsPsychologyPolitical scienceComputer science

Abstract

fetched live from OpenAlex

The need to establish and maintain good rapport with interviewees is a methodological axiom supported by most social scientists. Some say we place unnecessary limits on data collection, however, when respondents' statements are simply accommodated. More innovative approaches are especially needed to account for varying roles and their narratives, as Goffman would have it, at different frontstage and backstage levels. Sociological focus on tolerable deviance—with emphasis on public deviance by those who promote wider tolerance through situated claims making—presents a research challenge of this nature. The interviews in this article with tattoo artists and drug reform advocates combine attention to rapport with more confrontational tactics, aiming to elicit from informants an array of interpretive standpoints. The authors term this technique “good cop, bad cop.”

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)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.827
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.738
GPT teacher head0.618
Teacher spread0.120 · 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