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Record W4254710616 · doi:10.1002/ltl.20021

Intentional leadership

2012· article· en· W4254710616 on OpenAlexaff
Jeremie Kubicek

Bibliographic record

VenueLeader to Leader · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicEducation, Leadership, and Health Research
Canadian institutionsImpact
Fundersnot available
KeywordsRaising (metalworking)Perspective (graphical)Action (physics)Public relationsWork (physics)Process managementBusinessKnowledge managementPsychologyPolitical scienceComputer scienceEngineering

Abstract

fetched live from OpenAlex

Abstract Leadership development often lacks continuity, strategy, and perspective. Kubicek asserts that what is needed is more holistic thinking, understanding that “raising leaders is not a program; it is a way of life.” Leaders must be intentional about raising capacity and improving capabilities. One way is to be more intentional about the use of time, especially by getting more out of what he refers to as “informal time.” Building development into such segments as exercise and driving to work provides a boost of “trading up” to a new level of thought and action.

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)0.004
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0050.003
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0260.006

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 head0.458
GPT teacher head0.492
Teacher spread0.033 · 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 designNot applicable
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

Citations2
Published2012
Admission routes1
Has abstractyes

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