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Record W4408489492 · doi:10.70150/2654b605

The Machiavellian Challenge to Business Ethics

2025· article· en· W4408489492 on OpenAlexaff
George Bragues

Bibliographic record

VenueEthical Review of Social Sciences · 2025
Typearticle
Languageen
FieldDecision Sciences
TopicEthics in Business and Education
Canadian institutionsUniversity of Guelph-Humber
Fundersnot available
KeywordsBusiness ethicsEngineering ethicsPhilosophyEnvironmental ethicsBusinessPolitical sciencePublic relationsEngineering

Abstract

fetched live from OpenAlex

No political philosopher is better known in the business world than Niccolo Machiavelli. His fame resting on The Prince, the Renaissance Italian writer has often been featured in the popular business press, mostly to show the relevance of his realpolitik world-view to the sorts of issues that a contemporary manager is apt to face. However, the popular view of Machiavelli as a hard-headed thinker has been challenged by scholars pointing to his advocacy of republics in the Discourses on Livy, his other great work. Interpreted along these lines, Machiavelli can be invoked to support participatory structures in business along with the cultivation of publicly spirited virtues. We argue that the common perceptions of Machiavelli are actually on a better track. His analysis of republics uncovers weaknesses germane to business that render The Prince more suitable to commercial life. As such, Machiavelli’s overriding point is that in a competitive arena, such as that of modern-day business, individuals holding leadership positions, or aspiring to them, must be prepared to go beyond conventional morality and live by a different and, indeed, icy set of rules. Being good in business, Machiavelli warns, will only lead to personal ruin. Machiavelli goes further than this, calling for a trans-valuation of values, wherein the praiseworthy quality of leaders are redefined so as to take into account the competitive realities of business. In this new ethic, virtue is connected to acquisitiveness, moral flexibility, image management, and reaches its culmination in the entrepreneurial task of founding a great company.

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)0.008
metaresearch head score (Gemma)0.009
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: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0080.061
Scholarly communication0.0130.007
Open science0.0010.005
Research integrity0.0070.012
Insufficient payload (model declined to judge)0.0020.001

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 head0.388
GPT teacher head0.562
Teacher spread0.174 · 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
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
Published2025
Admission routes1
Has abstractyes

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