Facilitating learning of the peer-review process through a student-led undergraduate journal
Bibliographic record
Abstract
Conventionally, undergraduate science students engage in learning through didactic methods. This can present science as an indisputable collection of knowledge, rather than an ongoing process of discovery. By increasing students’ exposure to scientific processes, undergraduate science programs can enable students to understand the complexities of navigating scientific knowledge with a critical mindset. To facilitate this process, we implemented a student-led undergraduate peer-reviewed journal, The Child Health Interdisciplinary Literature & Discovery Journal, in the Child Health Specialization of McMaster University’s Honours Health Sciences (BHSc) Program. This case study discusses the development and implementation of this student-led journal within an inquiry-based learning curriculum. We aim to promote an understanding of curricular co-creation as a mechanism for enhancing student learning of scientific processes and the development of critical thinking, information literacy, and collaboration skills. We seek to inspire innovative teaching and learning strategies in higher education wherein students are active partners in the learning process.
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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 | 0.053 | 0.161 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".