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Record W1977022467 · doi:10.1177/1094428114565028

What Grounded Theory Is…A Critically Reflective Conversation Among Scholars

2015· article· en· W1977022467 on OpenAlexaff
Isabelle Walsh, Judith A. Holton, Lotte Bailyn, Walter Fernández, Natalia Levina, Barney G. Glaser

Bibliographic record

VenueOrganizational Research Methods · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Applications
Canadian institutionsMount Allison University
Fundersnot available
KeywordsGrounded theoryConversationScope (computer science)CreativityEpistemologySociologyQualitative researchEngineering ethicsPsychologyComputer scienceSocial psychologySocial science

Abstract

fetched live from OpenAlex

Grounded theory (GT) is taught in many doctoral schools across the world and exemplified in most methodological books and publications in top-tier journals as a qualitative research method. This limited view of GT does not allow full use of possible resources and restrains researchers’ creativity and capabilities. Thus, it blocks some innovative possibilities and the emergence of valuable theories, which are badly needed. Therefore, understanding the full reach and scope of GT is becoming urgent, and we brought together a panel of established grounded theory scholars to help us in this endeavor through a reflective conversation.

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)0.154
metaresearch head score (Gemma)0.158
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.846
Threshold uncertainty score0.814

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1540.158
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0060.005
Science and technology studies0.0070.059
Scholarly communication0.0310.021
Open science0.0060.009
Research integrity0.0100.022
Insufficient payload (model declined to judge)0.0040.003

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 head0.471
GPT teacher head0.678
Teacher spread0.207 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
DomainMethods
GenreEmpirical

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

Citations258
Published2015
Admission routes1
Has abstractyes

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