Bibliographic record
Abstract
LettersJuly 2022A Legacy of Scientific RacismCharles S. Bryan, MD and Richard D. deShazo, MDCharles S. Bryan, MDDepartment of Medicine, University of South Carolina School of Medicine, Columbia, South CarolinaSearch for more papers by this author and Richard D. deShazo, MDDepartment of Medical Education, The University of Alabama School of Medicine at Birmingham, and Departments of Medicine and Pediatrics, The University of Mississippi Medical Center, Birmingham, Alabama, and Jackson, MississippiSearch for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/L22-0137 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail IN RESPONSE: We thank Dr. Nurhussein for his interest, views on racial reckoning, and contrasting of William Osler with Benjamin Rush.Elsewhere, we have contextualized Osler's racial transgressions as seen through a 21st-century lens (1, 2). Osler's alleged statement that Canada is a “white man's country” offends today; however, in May 1914, White Canadians overwhelmingly felt that way (2). Concerning lobar pneumonia, Osler reported without comment in the 7th edition of The Principles and Practice of Medicine that mortality at the Johns Hopkins Hospital averaged “about 25 percent” in White persons but was “rarely under 30 percent” in Black persons. ...References1. Bryan CS, ed. Sir William Osler: An Encyclopedia. Norman Pub/HistoryofScience.com; 2020. Google Scholar2. Bryan CS. Sir William Osler, eugenics, racism, and the Komagata Maru incident. Proc (Bayl Univ Med Cent). 2020;34:194-8. [PMID: 33456199] doi:10.1080/08998280.2020.1843380 CrossrefMedlineGoogle Scholar3. Fiddes P. The Myth of William Osler: A Re-Examination of the Legacies of a Medical Legend. Austin Macauley Pub; 2021. Google Scholar4. Driggers EA. The chemistry of blackness: Benjamin Rush, Thomas Jefferson, Everard Home, and the project of defining blackness through chemical explanations. Critical Philosophy of Race. 2019;7: 372-91. Accessed at https://scholarlypublishingcollective.org/psup/cpr/article/7/2/372/199969/The-Chemistry-of-Blackness-Benjamin-Rush-Thomas on 20 February 2022. Google Scholar5. Dufresne T. The Democracy of Suffering: Life on the Edge of Catastrophe, Philosophy in the Anthropocene. McGill-Queen's Univ Pr; 2019. Google Scholar Author, Article, and Disclosure InformationAffiliations: Department of Medicine, University of South Carolina School of Medicine, Columbia, South CarolinaDepartment of Medical Education, The University of Alabama School of Medicine at Birmingham, and Departments of Medicine and Pediatrics, The University of Mississippi Medical Center, Birmingham, Alabama, and Jackson, MississippiDisclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M21-3474. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoA Legacy of Scientific Racism: William Osler's “An Alabama Student” Charles S. Bryan , Richard D. deShazo , and Margaret W. Balch A Legacy of Scientific Racism Mohammed A. Nurhussein Metrics July 2022Volume 175, Issue 7Page: W69-W70KeywordsArchivesLibrariesRacial and ethnic issuesRiversSurgeons ePublished: 19 July 2022 Issue Published: July 2022 Copyright & PermissionsCopyright © 2022 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.023 | 0.038 |
| Insufficient payload (model declined to judge) | 0.027 | 0.009 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".