A student-run peer-reviewed journal: an educational tool for students in the health sciences
Bibliographic record
Abstract
Raywat Deonandan1, Premal Patel2, Robyn Winterbottom31Interdisciplinary School of Health Sciences, University of Ottawa, Ottawa, Ontario, 2Faculty of Medicine, University of Calgary, Calgary, Alberta, 3School of Medicine, McMaster University, Hamilton, Ontario, CanadaAbstract: Students at the University of Ottawa, many of whom were targeting a career in medicine, were surveyed to determine their attitudes and expectations regarding a new student-run peer-reviewed journal for the health sciences. A number of students reported that the existence of the journal would make them more likely to take a class with a written component, while a majority would work harder on that assignment. Those intending to pursue postgraduate or professional studies were most likely to recognize the value to their careers of having a publication history. We argue that student-run medical communication endeavors such as this are beneficial both for enhancing student careers and for contributing to a more thorough educational experience.Keywords: journal, literacy, publication, student, undergraduate, education
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 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 | 0.032 | 0.200 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.034 | 0.011 |
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".