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Record W2588998240 · doi:10.1002/joe.21777

Spiritual Intelligence: Going Beyond IQ and EQ to Develop Resilient Leaders

2017· article· en· W2588998240 on OpenAlexaboutno aff
Stephen K. Hacker, Marvin Washington

Bibliographic record

VenueGlobal Business and Organizational Excellence · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Spirituality and Leadership
Canadian institutionsnot available
Fundersnot available
KeywordsEmotional intelligenceCompetence (human resources)PsychologyLeadership developmentCurriculumSpiritual intelligenceApplied psychologyMedical educationManagementPedagogyPublic relationsSocial psychologyPolitical scienceMedicine

Abstract

fetched live from OpenAlex

University‐based leadership development programs have long included a focus on human intelligence and emotional intelligence to foster subject and relationship competence, respectively. In response to the need to develop leaders with a strong sense of individual purpose, vision, and values who can meet the challenges of a volatile business environment, spiritual intelligence, a measure of inner resilience, is being added to executive training curricula. All three elements were addressed in a four‐year leadership development program conducted through the University of Alberta for the Alberta Heath Services and the Royal Canadian Mounted Police. The results of post‐program self‐assessments and 360‐degree evaluations of the 160 program participants highlight the value of this three‐tier training method in molding a new generation of resilient leaders. © 2017 Wiley Periodicals, Inc.

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 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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.048
GPT teacher head0.322
Teacher spread0.273 · 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 teacher head, not a consensus.

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

Citations23
Published2017
Admission routes1
Has abstractyes

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