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CEO Prestige and Strategic Deviance

2012· article· en· W2901258972 on OpenAlexaff
Russell Fralich, Carrie Qi

Bibliographic record

VenueAcademy of Management Proceedings · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsPrestigeDeviance (statistics)LegitimacyAction (physics)Social capitalFace (sociological concept)Sample (material)Social psychologyBusinessPositive economicsPolitical sciencePublic relationsSociologyEconomicsPsychologyLawPoliticsSocial science

Abstract

fetched live from OpenAlex

Do prestigious CEOs engage in more deviant strategic action? Arguments built on upper echelon, neo-institutional, social capital and human capital theories make two contrasting predictions based on the likelihood of threats to legitimacy. On one hand, prestigious CEOs will engage in more deviant strategic action because they are more easily forgiven, and face lower levels of threat to their organization’s legitimacy in the case of failure. However, they may also act more isomorphically with other firms because they fear loss of prestige. We test the relationship between CEO prestige and non-isomorphic or deviant strategic action, using a sample of CEOs of S&P 500 firms between 2005-2009. Our results suggest that CEOs with prestige arising from human capital tend to make more deviant strategic responses, but no relationship was found with prestige due to social capital.

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)0.011
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.039
GPT teacher head0.236
Teacher spread0.197 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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