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Record W3126443410 · doi:10.1108/jocm-07-2018-0190

Miles and Snow Typology: most influential journals, articles, authors and subject areas

2021· article· en· W3126443410 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

VenueJournal of Organizational Change Management · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsTypologySubject (documents)CitationOriginalitySociologyValue (mathematics)Multidisciplinary approachLibrary scienceCitation analysisMarketingSocial scienceComputer scienceBusinessQualitative researchMathematicsStatistics

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to find out the most influential journals, articles, authors and the subject areas where Miles and Snow typology is used. The study identifies the opportunities for future research as well. Design/methodology/approach Review is based on 196 journal articles selected through a systematic and rigorous search process from the four databases: ProQuest, Business Source Complete, Willy and Science Direct. Total Citation, threshold citations, fractional citation and citation per year techniques are used for analyses. Findings Strategic Management Journal (SMJ), Academy of Management Journal (AMJ) and Journal of Marketing (JOM) are the most influential Journals. The most influential and prolific articles on the subject are from Hambrick (1983), Conant et al. (1990), Doty et al. (1993), Sabherwal et al. (2001), Desarbo et al. (2005) and Fiss (2011). Management, strategic management and marketing are the most studied subject areas. Originality/value Although there have been many reviews of the literature on this typology, the systematic review on Miles and Snow typology to find out the most influential journals, authors, articles and subject area has not been done before.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.738
Threshold uncertainty score0.655

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.246
Teacher spread0.212 · 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