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Record W4412199202 · doi:10.1080/14719037.2025.2531895

A convergence of executive management styles? new elements of comparison

2025· article· en· W4412199202 on OpenAlexaffabout
Mauro Tebaldi, Marco Calaresu, Chiara De Micheli, Patrice Dutil, Andrea Migone

Bibliographic record

VenuePublic Management Review · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal and Cross-Cultural Management
Canadian institutionsSimon Fraser UniversityToronto Metropolitan University
FundersEuropean Commission
KeywordsConvergence (economics)AccountingBusinessEconomicsMacroeconomics

Abstract

fetched live from OpenAlex

We compare the Italian Directors General and Canadian Deputy Ministers’ use of time during their average work week using a survey instrument and propose a four-fold categorization of managerial styles. We find that the activities of top executives in the two countries differ, but not dramatically. In particular, we find a very close match in time devoted to ‘administrative’ tasks and confirm that, in general, these executives have relatively limited time for strategic and long-term planning. The data suggest that ‘relational’ approaches, which focus on connecting to the personnel of the organization, appear important in how top administrative executives shape their work.

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)0.018
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0100.009
Science and technology studies0.0010.003
Scholarly communication0.0040.006
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.035
GPT teacher head0.379
Teacher spread0.344 · 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 designObservational
Domainnot available
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

Citations1
Published2025
Admission routes2
Has abstractyes

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