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Record W2076895300 · doi:10.1108/01437720610652862

Why leaders fail: exploring the darkside

2006· article· en· W2076895300 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Manpower · 2006
Typearticle
Languageen
FieldDecision Sciences
TopicLeadership, Behavior, and Decision-Making Studies
Canadian institutionsYork University
Fundersnot available
KeywordsSelfishnessOriginalityValue (mathematics)Remedial educationPublic relationsSociologyPsychologyPositive economicsPolitical scienceSocial psychologyEconomicsLawComputer science

Abstract

fetched live from OpenAlex

Purpose With half of those in leadership positions maybe falling short, the purpose of this paper is to review literature on why leaders fail. Design/methodology/approach A number of recent journal articles, book chapters and books were examined. Findings The paper identified common causes of failure and possible remedial actions. Leaders that fail behave in ways reflective of their personality that limit or derail their careers. These flaws include arrogance, aloofness, perfectionism, insensitivity, selfishness and betraying the trust of others. Research limitations/implications Very little research on this important topic has been conducted. Practical implications Solutions highlight the role of early feedback in reducing leadership failures. Originality/value This paper raises a topic important in leadership development but ignored by both researchers and managers.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.550

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.239
GPT teacher head0.416
Teacher spread0.177 · 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