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Record W2095501868 · doi:10.1353/utq.0.0260

McGill Medicine (review)

2008· article· en· W2095501868 on OpenAlexvenueaboutno aff
Delia Gavrus

Bibliographic record

VenueUniversity of Toronto Quarterly · 2008
Typearticle
Languageen
FieldMedicine
TopicHistory of Medical Practice
Canadian institutionsnot available
Fundersnot available
KeywordsPeriod (music)History of medicineHistoryClassicsMedicineGerontologyLibrary scienceArt

Abstract

fetched live from OpenAlex

Reviewed by: McGill Medicine Delia Gavrus Joseph Hanaway, Richard Cruess, and James Darragh. McGill Medicine. Volume 1885–1936 McGill-Queen's University Press. xix, 315. $60.00 Professor of neurology Joseph Hanaway, former McGill University dean of medicine Richard Cruess, and former associate dean James Darragh have written a sweeping history of one the most prestigious medical schools in Canada. The second volume covers the period 1885–1936, an eventful and uneven time in the history of the Faculty of Medicine at McGill University (the first volume was written by Hanaway and Cruess, and it dealt with the school's first half century, 1829–1885). The second volume first chronicles a period of expansion (1885–1901), in which increased student enrolment led to an increase in laboratory space and a doubling in the size of the Medical Building, followed by a period of evaluation and change that saw the rise of experimental medicine (1901–14). The authors argue persuasively that the 1910 Flexner Report on the state of medical education in the United States and Canada was not the primary stimulus for the changes that occurred at McGill. Rather, the work of Dean Francis Shepherd and his staff, as well as the financial help of several important benefactors, was the essential catalyst for this change. The Flexner Report with its stress on pre-clinical science education did, however, enable McGill to carry on a lack of emphasis on clinical training, a slight that continued until the interwar period. Help from the Rockefeller Foundation in the 1920s and 1930s, as well as the leadership of Dean Charles Martin, whom the authors describe as a decision maker and a good leader, resulted in many new developments, [End Page 291] such as the establishment of the Montreal Neurological Institute and the inauguration of the Osler Library. The latter part of the volume continues to chart the growth of various medical subjects (e.g., anatomy, pharmacology, neurosurgery, public health), but the treatment of some of these specialties feels rushed and incomplete. The volume concludes with a brief chapter on the governance of the medical faculty between 1885 and 1936. This book is an excellent source of information for those interested in the history of medical education in Canada. It is most useful as a reference book; the authors' good use of subheadings makes looking up specific information very easy. The helpful appendices include biographical sketches of the main individuals introduced in the book, as well as lists of officers of the McGill Faculty of Medicine and the Holmes and Wood gold medalists. The book does have, however, several weaknesses that leave more room for future work on this topic. Secondary sources are mined only for factual details, and the professional history of medicine literature is used very little, if at all. The main focus of this volume is on administration, on the contributions of individuals associated with the medical school (deans, physicians, university principals), and on the changing curriculum. There is little analysis, framework, or historical argument, and as such this book contributes little to historiography. Furthermore, the book sometimes feels burdened with unnecessary details (e.g., the list of when and whom Dean Francis Shepherd's children married). Despite these shortcomings, the three authors have produced a well-researched, informative, and much-needed history of a great Canadian medical school. Delia Gavrus Institute for the History and Philosophy of Science and Technology, University of Toronto Copyright © 2008 University of Toronto Press Incorporated

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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.809
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.000

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 head0.023
GPT teacher head0.248
Teacher spread0.225 · 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
Published2008
Admission routes2
Has abstractyes

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