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Advances in Strategic Management

2012· book-chapter· en· W4292223157 on OpenAlexaff
Steven Kahl, Brian S. Silverman, Michael A. Cusumano

Bibliographic record

VenueAdvances in strategic management · 2012
Typebook-chapter
Languageen
FieldSocial Sciences
TopicGlobal and Cross-Cultural Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPublishingStrategic managementPoliticsIdeologyBusiness historyCitationPolitical scienceManagementBusinessPublic relationsMarketingEconomicsLaw

Abstract

fetched live from OpenAlex

Citation (2012), "Advances in Strategic Management", Kahl, S.J., Silverman, B.S. and Cusumano, M.A. (Ed.) History and Strategy (Advances in Strategic Management, Vol. 29), Emerald Group Publishing Limited, Bingley, p. iii. https://doi.org/10.1108/S0742-3322(2012)0000029017 Publisher: Emerald Group Publishing Limited Copyright © 2012, Emerald Group Publishing Limited Book Chapters History and Strategy Advances in Strategic Management Advances in Strategic Management Copyright Page List of Contributors The Integration of History and Strategy Research Economic Experiments and the Development of Wi-Fi Platforms Versus Products: Observations from the Literature and History Patent Pools: Licensing Strategies in the Absence of Regulation Marrying History and Social Science in Strategy Research The Evolution of Alternative Business Models and the Legitimization of Universal Credit Card Industry: Exploring the Contested Terrain where History and Strategy Meet Strategy Followed Structure: Management Consulting and the Creation of a Market for “Strategy,” 1950–2000 Strategy, Ideology, and Structure: The Political Processes of Introducing the M-form in two Dutch Banks History in Strategy Research: what, why, and how? Audience Structure and the Failure of Institutional Entrepreneurship Orphaned Jazz: Short-Lived Start-ups and the Long-Run Success of Depression-Era Cultural Products

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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: Review · Consensus signal: none
Teacher disagreement score0.040
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.007
Science and technology studies0.0020.005
Scholarly communication0.0090.008
Open science0.0010.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0400.019

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 head0.033
GPT teacher head0.323
Teacher spread0.290 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations67
Published2012
Admission routes1
Has abstractyes

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