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Record W3127212551 · doi:10.1177/1476127020985094

Navigating the tensions of quality in qualitative research

2021· article· en· W3127212551 on OpenAlexaff
Paula Jarzabkowski, Ann Langley, Amit Nigam

Bibliographic record

VenueStrategic Organization · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsCraftQuality (philosophy)CreativityQualitative researchAccountabilityProcess (computing)Public relationsSociologyEngineering ethicsKnowledge managementProcess managementPolitical scienceBusinessComputer sciencePsychologyEpistemologyEngineeringSocial scienceSocial psychology

Abstract

fetched live from OpenAlex

In this essay that serves to introduce the So!apbox Forum on quality in qualitative research, we argue that achieving quality involves a process of navigating the tensions between structure and creativity, and between accountability and professionalism. Guidelines for achieving quality such as those offered in this forum or elsewhere should not therefore be seen as absolute standards, templates or checklists to be strictly followed, but rather as toolkits that can assist in navigating the tensions involved in participating in and developing the qualitative research craft as a community of scholars, reviewers and editors.

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)0.715
metaresearch head score (Gemma)0.645
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.285
Threshold uncertainty score0.352

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.7150.645
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0090.007
Science and technology studies0.0360.176
Scholarly communication0.0460.061
Open science0.0090.056
Research integrity0.0230.042
Insufficient payload (model declined to judge)0.0050.001

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 head0.635
GPT teacher head0.690
Teacher spread0.054 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainMethods
GenreMethods

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

Citations35
Published2021
Admission routes1
Has abstractyes

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