Plagiarism in Residency Application Essays
Bibliographic record
Abstract
Letters7 December 2010Plagiarism in Residency Application EssaysSameer Siddique, MD, Harris V. Naina, MD, and Samar Harris, MDSameer Siddique, MDFrom Albert Einstein Medical Center, Philadelphia, PA 19141, and University of Texas Southwestern Medical Center at Dallas, Dallas, TX 75390.Search for more papers by this author, Harris V. Naina, MDFrom Albert Einstein Medical Center, Philadelphia, PA 19141, and University of Texas Southwestern Medical Center at Dallas, Dallas, TX 75390.Search for more papers by this author, and Samar Harris, MDFrom Albert Einstein Medical Center, Philadelphia, PA 19141, and University of Texas Southwestern Medical Center at Dallas, Dallas, TX 75390.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-153-11-201012070-00019 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail TO THE EDITOR:Although Segal and colleagues (1) must be congratulated for their study in converting long-held suspicions to hard research evidence, we feel that their conclusions are simplistic and do not address several issues.First, although most international medical graduates come from places where English is not their first language and are culturally and socially different from U.S. or Canadian graduates, this does not in any way imply that plagiarism there is more socially acceptable or is less of an ethical crime than in the Western world.Second, in a competitive field of professionals, each displaying similar traits to ...References1. Segal S, Gelfand BJ, Hurwitz S, Berkowitz L, Ashley SW, Nadel ES, et al. Plagiarism in residency application essays. Ann Intern Med. 2010;153:112-20. [PMID: 20643991] LinkGoogle Scholar2. Mowatt G, Shirran L, Grimshaw JM, Rennie D, Flanagin A, Yank V, et al. Prevalence of honorary and ghost authorship in Cochrane reviews. JAMA. 2002;287:2769-71. [PMID: 12038907] CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAffiliations: From Albert Einstein Medical Center, Philadelphia, PA 19141, and University of Texas Southwestern Medical Center at Dallas, Dallas, TX 75390.Disclosures: None disclosed. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoPlagiarism in Residency Application Essays Scott Segal , Brian J. Gelfand , Shelley Hurwitz , Lori Berkowitz , Stanley W. Ashley , Eric S. Nadel , and Joel T. Katz Plagiarism in Residency Application Essays Moxie Stratton-Loeffler Plagiarism in Residency Application Essays Jonas B. Green Plagiarism in Residency Application Essays Michael Kirsch Plagiarism in Residency Application Essays Jason P. Lott Response to Comments on Plagiarism in Residency Application Essays Scott Segal , Brian J. Gelfand , and Joel T. Katz Metrics Cited byPlagiarised letters of recommendation submitted for the National Resident Matching ProgramResponse to Comments on Plagiarism in Residency Application EssaysScott Segal, MD, MHCM, Brian J. Gelfand, MD, and Joel T. Katz, MD 7 December 2010Volume 153, Issue 11Page: 765-766KeywordsConflicts of interestCrimeForecastingGraduate medical educationMotivationResidencyTaste ePublished: 7 December 2010 Issue Published: 7 December 2010 Copyright & PermissionsCopyright © 2010 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Research integrity Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Research integrity Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".