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Record W3108462903 · doi:10.1007/978-3-319-62114-2

The Palgrave Handbook of Management History

2020· book· en· W3108462903 on OpenAlexaff
Bradley Bowden, Jeffrey Muldoon, Anthony M. Gould, Adela McMurray

Bibliographic record

Venuenot available
Typebook
Languageen
FieldBusiness, Management and Accounting
TopicManagement Theory and Practice
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHistory

Abstract

fetched live from OpenAlex

This Handbook is the definitive source and reference tool for academics, researchers and graduate students working in the field of Management History. Consisting of eleven sections, they will collectively cover management history’s past and present and provide an unparalleled overview of both managerial practice and thought. As a discipline, management history has relatively recently splintered from business history, focusing on the study of organizations and the ways in which work is structured and managed. Initially employing a heavily western perspective and influenced mainly by British and American historians, the discipline has expanded the focus of its studies both temporally and geographically to incorporate pre-19th century forms of organization and extend its scope beyond Western Europe and North America. This important project will be a high level, systematic and comprehensive tool thanks to the range of contributions from leading experts and academics. It is intended to be the first port of call for all research endeavors in the field of management history.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.129
Threshold uncertainty score0.431

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.007
Science and technology studies0.0020.002
Scholarly communication0.0060.005
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.1290.069

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 head0.022
GPT teacher head0.193
Teacher spread0.171 · 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 designNot applicable
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

Citations21
Published2020
Admission routes1
Has abstractno

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