A dialogue with editors, past and present, on how the CJS came of age.
Bibliographic record
Abstract
by G.L. Warnock Seldom does an opportunity arise to summarize 50 years of history with direct input from people who have been leaders in molding the direction and growth of a major journal. Therefore, as part of the 50th anniversary of the Canadian Journal of Surgery (CJS), the editorial board endorsed the concept of interviewing editors, past and present. We aimed to follow up on the inaugural editorial authored by Dr. Robert M. Janes in 1957 and determine how the Journal has lived up to its reputation and what challenges were encountered through its years of growth. A series of interview questions grew naturally from the readership survey of 2006 (summarized elsewhere in this anniversary section). To offer some perspective on the challenges faced by the editors-in-chief, the editorial boards and the managing editors, these questions covered the organization and governance of the Journal, including finances, journal content, readership opinions, challenges and the quality and significance of the CJS. Former editors Drs. C. Barber Mueller, Lloyd D. MacLean, Roger G. Keith and Jonathan L. Meakins, as well as current editor Dr. James P. Waddell and former managing editor Gillian Pancirov, were contacted by teleconference. The questions were reviewed by Dr. Nis Schmidt and Ms. Rachel Cadelina. Final transcripts of the interviews were lightly edited and reproduced in the sections that follow. During the course of the interviews, 2 important observations emerged. First, the Journal has remained under the stewardship of very solid board chairmen or coeditors who have steered it through turbulent and challenging times. All of the editors, past and present, are unanimous in one observation — a solid acknowledgement of former managing editor, Gillian Pancirov. The praise for Gillian's effort remains effusive for the roles that she played to maintain a high-quality reputable journal of surgical scholarship. A second major observation is the acknowledgement of solid enduring quality, which informs the peer group of Canadian surgeons about the science and practice of surgery across many surgical disciplines in Canada. This unique perspective on Canadian surgery is unparalleled among national surgical journals in Canada. Finally, these largely unedited transcripts chronicle many challenges in bringing a high-quality journal to its readers through decades of solid leadership and contributions from coast to coast in Canada.
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How this classification was reachedexpand
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 | 0.002 | 0.007 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedMachine predicted; a candidate call from one teacher head, 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".