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Record W4387231830 · doi:10.37964/cr24770

Physician leadership during the pandemic: reflections from hospitalist leaders in British Columbia, Canada: a mixed-methods evaluation study

2023· article· en· W4387231830 on OpenAlexvenueaboutno aff
Vandad Yousefi

Bibliographic record

VenueCanadian Journal of Physician Leadership · 2023
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsStaffingPandemicHealth careNursingCoronavirus disease 2019 (COVID-19)MedicineFace (sociological concept)Public relationsPolitical scienceFamily medicineSociology

Abstract

fetched live from OpenAlex

Hospitalist physician leaders play an important role in how health care organizations deliver acute care services. Understanding the challenges they face can be important in preparing them for future crises. Methods: We conducted a mixed-methods evaluation study to explore the challenges faced by hospitalist leaders and the impact of the COVID-19 pandemic on their ability to address them. Results: Our findings suggest that staffing issues are a major concern, along with the quality of relations between physicians and health authority managers. Moreover, our findings suggest a need for more leadership training for hospitalists. Conclusions: Hospitalist physician leaders in British Columbia face significant challenges in staffing their programs, as well as difficult relations with administrators. Efforts to improve collaboration and physician engagement should be a high priority for health system leaders in the province.

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)0.037
metaresearch head score (Gemma)0.041
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.489

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0110.002
Scholarly communication0.0040.001
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.334
GPT teacher head0.459
Teacher spread0.125 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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