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Record W2066054724 · doi:10.1177/1742715007079311

Leadership and Succession: The Challenge to Succeed and the Vortex of Failure

2007· article· en· W2066054724 on OpenAlexaffabout
Bryan J. Poulin, Michael Z. Hackman, Carmen Barbarasa-Mihai

Bibliographic record

VenueLeadership · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsLakehead University
Fundersnot available
KeywordsLeadership studiesPublic relationsEcological successionTransactional leadershipLeadership developmentSuccession planningShared leadershipLeadershipLeadership styleNeuroleadershipServant leadershipEmpirical researchSociologyPolitical scienceManagementEpistemologyEconomics

Abstract

fetched live from OpenAlex

Despite a large number of studies concerned with leadership and leadership succession — of which more than 200 have addressed the latter — results have been inconsistent and inconclusive. One suggestion from the literature was to conduct more qualitative case research as a supplement to the many empirical survey studies which have been published. The present study explored, at first hand, eight firms that opinion leaders had identified as successful (six in New Zealand, one in Canada, one in the United States) and another seven US firms studied by others that had once been touted as successful. Two patterns emerged: (1) socialized leadership relationships succeeded in transforming the firm by applying leadership and management principles to serve the needs of others, and enlisting support throughout and beyond the firm; and (2) personalized leadership relationships promised much and either achieved success, narrowly defined, or failed completely. The conclusion: socialized leadership relations matter critically. Recommendations are offered for leadership succession and future research.

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)0.016
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.013
Scholarly communication0.0080.006
Open science0.0010.004
Research integrity0.0010.002
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 head0.064
GPT teacher head0.243
Teacher spread0.179 · 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
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

Citations34
Published2007
Admission routes2
Has abstractyes

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