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Record W2008716486 · doi:10.5430/jha.v3n3p33

The interpersonal skills of recent U.S. entrants to the field of healthcare management

2013· article· en· W2008716486 on OpenAlexvenueno aff
Diane Howard, Douglas M. Silverstein

Bibliographic record

VenueJournal of Hospital Administration · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Marketing Education
Canadian institutionsnot available
FundersRush University
KeywordsInterpersonal communicationHealth carePsychologySocial skillsSkills managementSenior managementPerceptionPublic relationsMedical educationNursingMedicinePolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

A national survey was conducted to determine the current state of senior executive perceptions of recent entrant managers within corporate headquarters, hospital systems, and freestanding hospitals. The survey was constructed based on leadership interpersonal competencies and competency-based career development programs. A total of 676 respondents returned a survey, representing 31% of the mailing sample. The goal of the research was to determine the perceptions that senior executives have about the interpersonal skills of recent entrants to the field of health care management and identify best practices for organizational training of such entrants. Findings reveal that senior executives view the recent entrant manager favorably regardless of age, gender, education, and non-clinical/clinical background. Senior executives also observed the need to require additional training of recent entrant managers in areas of management skills on understanding organizational politics, using a variety of techniques to influence others, handling difficult people or situations using diplomacy, confronting others about their mistakes, and exercising authority.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.488
Threshold uncertainty score0.203

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.007
GPT teacher head0.263
Teacher spread0.256 · 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.

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

Citations0
Published2013
Admission routes1
Has abstractyes

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