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The Qualitative Research Interview

2011· article· en· W3126054610 on OpenAlexaff
Sandy Qu, John Dumay

Bibliographic record

VenueRePEc: Research Papers in Economics · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsYork University
Fundersnot available
KeywordsInterviewQualitative researchReflexivitySemi-structured interviewOriginalityPerspective (graphical)SociologyEpistemologyPsychologyEngineering ethicsSocial scienceComputer science

Abstract

fetched live from OpenAlex

Purpose - Despite the growing pressure to encourage new ways of thinking about research methodology, only recently have interview methodologists begun to realize that “we cannot lift the results of interviewing out of the contexts in which they were gathered and claim them as objective data with no strings attached”. The purpose of this paper is to provide additional insight based on a critical reflection of the interview as a research method drawing upon Alvesson's discussion from the neopositivist, romanticist and localist interview perspectives. Specifically, the authors focus on critical reflections of three broad categories of a continuum of interview methods: structured, semi‐structured and unstructured interviews. Design/methodology/approach - The authors adopt a critical and reflexive approach to understanding the literature on interviews to develop alternative insights about the use of interviews as a qualitative research method. Findings - After examining the neopositivist (interview as a “tool”) and romanticist (interview as “human encounter”) perspectives on the use of the research interview, the authors adopt a localist perspective towards interviews and argue that the localist approach opens up alternative understanding of the interview process and the accounts produced provide additional insights. The insights are used to outline the skills researchers need to develop in applying the localist perspective to interviews. Originality/value - The paper provides an alternative perspective on the practice of conducting interviews, recognizing interviews as complex social and organizational phenomena rather than just a research method.

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)0.202
metaresearch head score (Gemma)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.912
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2020.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.009
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.003
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 head0.617
GPT teacher head0.636
Teacher spread0.019 · 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; both teacher heads agree on what is shown here.

Study designQualitative
Domainnot available
GenreOther

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

Citations6
Published2011
Admission routes1
Has abstractyes

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