Canada’s Student Journal Forum: From Humble Beginnings to National Conference
Bibliographic record
Abstract
Student Journal Forum began as an in-person half-day event at the University of Toronto (U of T) in 2015. It was organized by a group of librarians with the goal to connect editors of 60+ student-led U of T journals with publishing supports, best practices, and with each other. The audience’s enthusiastic engagement and the community-building power of the event prompted the librarians to offer it again the next year, and the year after. Eight years later, this local annual event has grown into a Canada-wide virtual gathering. The shift to online during the COVID-19 pandemic was a key catalyst to open the Forum to students to connect remotely, and for the event to be jointly organized by multiple libraries across Canada. The event’s offering has evolved as well, moving from librarian-led publishing best practice sessions to student-led presentations and participatory learning sessions. The most recent 2023 Forum featured an open call for proposals that let student editors share their experiences and present on topics that mattered to them. It was complemented by a half-day of publishing skill sessions presented by Canadian librarians and two panels with scholarly editors and publishing professionals. In this paper, we reflect on the evolution of the Student Journal Forum, its successes and challenges, and its role in establishing the connection between student editors across Canada and between different Canadian libraries that offer student journal publishing support.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.034 | 0.010 |
| Scholarly communication | 0.021 | 0.005 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".