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Record W3012912853 · doi:10.3138/cbmh.413-012020

Darwinian Evolution’s First 50 Years of Impact on Medicine and Botany at the University of Toronto, 1859 to 1909

2020· article· en· W3012912853 on OpenAlexafffundvenueabout
John Pm Court

Bibliographic record

VenueCanadian Journal of Health History · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Science and Natural History
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersUniversity of TorontoMcMaster University
KeywordsDarwinismEvolutionary medicineDarwin (ADL)Economic botanyCharles darwinClassicsLibrary scienceBiologyHistoryBotanyPlant ecologyEngineeringEvolutionary biology

Abstract

fetched live from OpenAlex

Prior to Darwin's masterworks, a university professor of medicine's purview generally included the professorship of botany and direction of the botanical gardens. Yet from the landmark 1876 Johns Hopkins model and especially after the 1910 Flexner Report, botany was limited at certain medical schools to (exaggerating somewhat) "decorating their lobbies!" Darwinian-era scientific paradigms spread from continental Europe through promulgators such as Huxley and Osler, transforming laboratory research, disease aetiology, biochemical therapeutics, and clinical "bedside" teaching. Unintended consequences at universities with medical schools might include altered loyalties and resources among competing disciplines. At the University of Toronto, botany vis-à-vis medicine was gradually treated as passé or secondary to zoology for modern, scientific platforms. This pattern was not universal; botany strongholds at universities such as Harvard continued to flourish. Where a negative perspective took hold with evolutionary impacts, botanists' careers became limited and the impetus for maintaining botanic research and teaching facilities such as a university botanical gardens was impaired.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.040
GPT teacher head0.224
Teacher spread0.184 · 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
Published2020
Admission routes4
Has abstractyes

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