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Record W3031276060

My Own Book Review

2015· article· en· W3031276060 on OpenAlexaff
Henry Mintzberg

Bibliographic record

VenueM n gement · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsPluralObjectivity (philosophy)Public relationsPrivate sectorWork (physics)Public sectorEpistemologySociologyPolitical scienceEngineeringLawLinguisticsPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Reviewing one’s own book is an interesting idea; finally a chance for some objectivity in a book review! I will review my first book The Nature of Managerial Work, (1973), together with my next-to-last one, Simply Managing (2013), because they address the same topic, 40 years apart. (In fact, Simply Managing is an abbreviated version of Managing, published in 2009, with some of the more formal material taken out.) The samples are different. The former was based on one week of observation of 5 chief executives, three of them in businesses, while the latter was based on a day of observation of 29 managers at all levels, more distributed across private, public, and plural sector organizations. The structure of the two books may appear to be similar, with a number of chapters paralleling each other, although some are in fact quite different. I shall review these similarities and differences, chapter by chapter, before asking in conclusion what I learned in these ensuing 40 years.

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)0.018
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: none
Teacher disagreement score0.094
Threshold uncertainty score0.315

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.006
Science and technology studies0.0010.001
Scholarly communication0.0070.005
Open science0.0020.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0940.108

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 head0.029
GPT teacher head0.230
Teacher spread0.201 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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