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Record W2313131617 · doi:10.15766/mep_2374-8265.9229

Family Medicine Curriculum in Quality Improvement, Management, and Leadership

2012· article· en· W2313131617 on OpenAlexaff
Philip Angus Ellison, Kate Hodgson, Mary-Kay Whittaker, Margaret Bucknam, Marcia Darling

Bibliographic record

VenueMedEdPORTAL · 2012
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFacilitatorCurriculumQuality managementMedical educationLibrary scienceSociologyManagementPsychologyMedicinePedagogyComputer scienceManagement system

Abstract

fetched live from OpenAlex

Abstract This resource provides excerpts and an overview description of a 4-day program teaching quality improvement in primary care, including the management and leadership of teams. Preconference work, along with excerpts from presenter guides, facilitator guides, and the participants' workbook for two of the 20 modules, are provided. Evaluations from previous presentations to residents and faculty of family medicine in 2011, as well as the agenda for 2012, are also included. The entire program with vision, mission, and learning objectives is described in an accompanying brochure. The work provides an educationally sound and highly interactive method of teaching the skills of quality improvement, with the management and leadership of teams, for a primary care setting.

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)0.002
metaresearch head score (Gemma)0.003
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: Methods · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0390.007

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 head0.272
GPT teacher head0.481
Teacher spread0.209 · 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
GenreMethods

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

Citations4
Published2012
Admission routes1
Has abstractyes

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