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Record W148280051

Dr. Frank W. Schofield: Veterinarian Extraordinaire

2008· article· en· W148280051 on OpenAlexaboutno aff
Craig W. Wilkinson

Bibliographic record

VenuePubMed Central · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsClassicsHistoryMedicine
DOInot available

Abstract

fetched live from OpenAlex

In this short book, the author provides a synopsis of the life of a colorful and influential pioneer of veterinary medicine in Canada. Dr. Frank Schofield was typical of many young men of the British Empire in the early 1900’s. Schofield was from a relatively poor middle-class family, and after a somewhat difficult childhood, he saw Canada as a land of opportunity, so at the age of 17 he left his family in England and emigrated to Canada. He worked on a farm for a short time to save money and then enrolled at the Ontario Veterinary College (OVC). The hardships he endured as a student were intense, and force the reader to reflect on the comparative luxury that most modern veterinary students enjoy in Canada. Schofield overcame poverty and debilitating illness during his studies at the OVC and excelled scholastically, though his sickness left him partially disabled for life. He then joined the OVC faculty as a veterinary researcher and teacher. As a professor of bacteriology and pathology at the OVC, Frank Schofield was known as a brilliant and insightful researcher, and as a spellbinding orator and teacher. However, he also had the reputation of being intimidating and opinionated, and he was feared and disliked by some students and colleagues. The long list of Frank Schofield’s publications provided as an appendix to the book underscores his pioneering work in determining the etiology and pathology of many common syndromes and diseases. His work involved investigations of nutritional conditions and many bacterial and viral infections including clostridial diseases, salmonellosis, and bovine mastitis. An appendix in the book contains an excerpt from the first “Schofield Memorial Lecture” at the OVC, and outlines Schofield’s contribution to the elucidation of the etiology and pathology of mouldy sweet clover poisoning. The description of some of the experiments that he conducted and the challenges he faced in pursuing this research is fascinating. Schofield’s dedication to service and sacrifice on behalf of veterinary research and education extended to his personal faith and service of God through service to humanity. He was known locally for his kindness and generosity, but few colleagues know of his long-term contributions to development in Korea. Early in his career, after working at OVC for several years, he went to Korea to teach bacteriology at a medical college in Seoul. While there, he traveled throughout the country as a Christian missionary, preaching the Gospel and encouraging the Koreans in their struggle for independence from Japanese rule. Though he returned to Canada and back to OVC after only 4 years, Frank Schofield continued throughout his life to support Korean orphanages, the church, and the efforts of Koreans to gain national independence. After his retirement, he returned to Korea to continue this work, and late in his life he was recognized by the South Korean government with the country’s highest civilian honor. This book is light reading and will be enjoyed by many who are interested in either the history of the veterinary profession in Canada, or the roles veterinarians play in developing nations. Frank Schofield’s influence has been felt directly by many who were his students during the decades he was a professor at the OVC. To this day, many Canadian veterinarians have probably been indirectly influenced by him through professors who were taught and mentored by him decades ago. This book makes an important contribution toward helping Canadian veterinarians remember our heritage.

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 categoriesScience and technology studies, Insufficient 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 score0.275
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 studies0.0010.001
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 head0.025
GPT teacher head0.226
Teacher spread0.201 · 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

Citations2
Published2008
Admission routes1
Has abstractyes

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