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University of Ottawa Department of Family Medicine Faculty Development Curriculum Framework

2013· book-chapter· en· W4248561104 on OpenAlexaffabout
Colla J. MacDonald, Martha McKeen, Donna Leith-Gudbranson, Madeleine Montpetit, Douglas Archibald, Christine Rivet, Rebecca J. Hogue, Mike Hirsh

Bibliographic record

VenueIGI Global eBooks · 2013
Typebook-chapter
Languageen
FieldSocial Sciences
TopicHigher Education Learning Practices
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCurriculumConsistency (knowledge bases)Medical educationQuality (philosophy)Engineering managementPlan (archaeology)Knowledge managementEngineeringMedicineComputer sciencePsychologyPedagogy

Abstract

fetched live from OpenAlex

In response to the challenges faced by rapid expansion and curriculum reform, the Department of Family Medicine (DFM) at the University of Ottawa (U of O) developed a Faculty Development Conceptual Framework (FDCF) and companion plan as a first step toward meeting the challenges of providing quality opportunities for the continuing professional development of preceptors in Family Medicine. The FDCF outlines the processes, opportunities and support structures needed to improve preceptors’ teaching skills and effectively deliver a newly revised “Triple C” competency-based curriculum. The FDCF acts as a quality standard to guide the design, delivery, and evaluation of a vibrant Faculty Development (FD) Program. It further provides a structure for implementing Enterprise Resource Planning (ERP) web applications to facilitate the flow of information between seven teaching sites, provide consistency among programs, and play a tactical role in the sharing of academic resources. This chapter introduces the DFM’s FDCF so other medical departments may benefit from the authors’ experiences and adapt or adopt the framework applications and methodologies to improve the effectiveness and efficiency of FD products and processes. Modifications to the framework are expected as this program continues to evolve.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.960
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.338
Teacher spread0.294 · 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.

Study designNot applicable
Domainnot available
GenreOther

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 routes2
Has abstractyes

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