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Situating and Constructing Diversity in Semi-Structured Interviews

2015· article· en· 827 citations· W2147417754 on OpenAlex· 10.1177/2333393615597674

Why is this work in the frame?

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

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Full frame distilled prediction

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.

Candidate categories
Metaresearch, Science and technology studies
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: QualitativeConsensus signal: Qualitative
Genre
Candidate signal: EmpiricalConsensus signal: Empirical
Teacher disagreement score
0.159
Threshold uncertainty score
1.000
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.917
GPT teacher head0.799
Teacher spread
0.118 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

Although semi-structured interviews (SSIs) are used extensively in research, scant attention is given to their diversity, underlying assumptions, construction, and broad applications to qualitative and mixed-method research. In this three-part article, we discuss the following: (a) how the SSI is situated historically including its evolution and diversification, (b) the principles of constructing SSIs, and (c) how SSIs are utilized as a stand-alone research method, and as strategy within a mixed-method design.

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.

The record

Venue
Global Qualitative Nursing Research
Topic
Health Policy Implementation Science
Field
Health Professions
Canadian institutions
Trent University
Funders
not available
Keywords
SituatedDiversity (politics)Diversification (marketing strategy)Qualitative researchSociologyEpistemologyData scienceComputer scienceSocial scienceMarketingArtificial intelligenceBusinessAnthropology
Has abstract in OpenAlex
yes