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Record W2754661373 · doi:10.1515/9780773590212-012

Health-Care Management in the Canadian Forces Health Services: A Comparative Study on Military and Civilian Health Leadership Skills

2013· book-chapter· en· W2754661373 on OpenAlexaboutno aff
Brenda Gamble, Olena Kapral, Paul Yielder

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2013
Typebook-chapter
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsHealth careEmotional intelligenceNursingPsychologyMedicinePolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

Three national surveys of Canadian health-care leaders were conducted to determine the views on the leadership skills necessary to lead in the hospital and com- munity/home-care setting. The electronic questionnaire distributed to members of the Canadian College of Health Leaders (N = 513), Canadian Home Care Association (N = 109), and Canadian Forces Health Services Group (N = 94) between 2010 and 2012 included items on demographic and employment characteristics and on leadership competencies. Competencies identified by all three groups were related to the concept of emotional intelligence. El as a psychodynamic tool provides the skills for health-care managers who lead integrated teams to provide an environment that ensures that each profession has an opportunity to contribute to its fullest capabilities.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.968
Threshold uncertainty score0.234

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.068
GPT teacher head0.308
Teacher spread0.241 · 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 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

Citations0
Published2013
Admission routes1
Has abstractyes

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