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Record W4380234755 · doi:10.1515/9780773576490-001

Preface

2009· book-chapter· en· W4380234755 on OpenAlexaboutno aff

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2009
Typebook-chapter
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

This book tells the story of the creation of the Northern Ontario School of Medicine (nosm), an important event in the history of medical education in Canada.The Ontario government announced the decision to create the school, with campuses at Laurentian University in Sudbury (the Northeast) and Lakehead University in Thunder Bay (the Northwest), in May 2001.The first students arrived on campus in September 2005.At the time of writing, the school has just received its full accreditation and is preparing to graduate its first class of students.Like all developments that mark a significant break with the past, this event had a highly visible public face, evident in the political debate that preceded it and the intense regional media interest that ensued.The public discourse was about the need for a bold gesture to redress the chronic shortage of doctors willing to practise in Northern Ontario.It touched a nerve in the resource-based communities of Northern Ontario, which had long felt alienated from the Southern Ontario monopoly over professional training programs -a monopoly that seemed more designed to meet metropolitan than rural needs.There were issues of regional pride and regional rivalries.But at a deeper level, the creation of a new school signalled changes in thinking about medical education that had been taking place for some time in various schools across Canada, the United States, and other parts of the world experiencing problems related to preparing physicians for practice in regions with dispersed populations.The fact that the new school started from a blank slate meant that its designers were able to incorporate many innovations (which had been proven in other contexts) into a new kind of program.The

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.488
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.5120.326

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 head0.037
GPT teacher head0.313
Teacher spread0.277 · 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.

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
Published2009
Admission routes1
Has abstractyes

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