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Record W2147331799 · doi:10.12927/hcpap..16894

Developing Leaders in the Real World

2003· review· en· W2147331799 on OpenAlexvenueno aff
David J. Fine

Bibliographic record

VenueA Nudge Too Far? A Nudge at All? On Paying People to Be Healthy · 2003
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicLeadership and Management in Organizations
Canadian institutionsnot available
Fundersnot available
KeywordsHealth careAdministration (probate law)Chief executive officerManagementCareer developmentPublic relationsMedical educationLeadership developmentOfficerPsychologyPolitical scienceEngineering ethicsMedicineEngineering

Abstract

fetched live from OpenAlex

Leatt and Porter present an excellent and timely review of the current leadership challenge in the field of healthcare administration. Their case is assembled through a review of relevant management literature and an adept summarization of current thinking and contemporary needs in the leadership zone of healthcare organizations. This commentator views the authors' thesis through the filters of a 30-year career as a healthcare administration practitioner and educator, the last 20 of which have been as a chief executive officer and concurrent professorial appointee at four universities in the United States. A leadership development paradigm at the UAB Health System is used to demonstrate an application of the lead authors' proposed, career-long development process encompassing graduate, postgraduate, mid-career and senior-executive levels.

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)0.005
metaresearch head score (Gemma)0.008
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: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0050.005
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.219
GPT teacher head0.369
Teacher spread0.151 · 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
GenreReview

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

Citations3
Published2003
Admission routes1
Has abstractyes

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