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Record W1549260995 · doi:10.3138/cbmh.21.1.5

“German Methods,” “Unconditional Gifts,” and the Full-Time System: The Case Study of the University of Toronto, 1919-23

2004· article· en· W1549260995 on OpenAlexvenueaboutno aff
Marianne Fedunkiw

Bibliographic record

VenueCanadian Journal of Health History · 2004
Typearticle
Languageen
FieldArts and Humanities
TopicMedical History and Research
Canadian institutionsnot available
Fundersnot available
KeywordsGermanGovernment (linguistics)AutonomyGuard (computer science)MedicineSociologyPolitical scienceMedia studiesLawHistory

Abstract

fetched live from OpenAlex

At the end of 1919, The University of Toronto got word that the Rockefeller Foundation was looking to give the university a gift of one million dollars (US) to "aid medical education.". This was in addition to a gift of $500,000 (Canadian) from merchant millionaires Sir John Craig and Lady Eaton. The implementation of the full-time system of clinical instruction made possible by these large gifts touched off a fiery debate among the medical profession and prompted a provincial government inquiry that would have thwarted long-awaited innovations in medical teaching and threatened the autonomy of the entire university. Much has been written about the full-time system of clinical medical education, most of it dealing with the United States. Some have documented cases where donor dollars were scorned in aiding the shift to full-time clinical teaching. Less well known is the tale of the University of Toronto. "The Provincial University" is an unique case study of a public university that tried to satisfy donor conditions even as it served its constituency- the people of Ontario. The challenge of implementing a new medical pedagogy between 1919 and 1923 was that Toronto lay at the centre of three poles: private versus public funding; "research" or laboratory medicine versus "experience" or "practical" medicine; and those who wanted to try the full-time system versus the established "old guard."

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)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.685
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.048
GPT teacher head0.279
Teacher spread0.231 · 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
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
Published2004
Admission routes2
Has abstractyes

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