Reimagining Scholarly Communication through Experiential Learning: Merging Theory and Practice for MLIS Students
Bibliographic record
Abstract
The lack of consistent training for scholarly authors, peer reviewers, and editors is a problem across disciplines, but it is one that affects academic librarians in a unique variety of ways. Like instructional faculty, academic librarians are generally required to engage in scholarly activity, but they are also increasingly in the position of providing guidance on and advocating for emerging trends in scholarly communication. This presentation will describe how the creation of a student-run journal and an associated scholarly communication course in Western University’s Faculty of Information and Media Studies (FIMS) are helping to meet this need. L'absence d'une formation cohérente pour les auteurs, les évaluateurs et les éditeurs des communications savantes, est un problème dans toutes les disciplines de recherche, mais aussi un problème qui affecte les bibliothécaires universitaires de différentes manières. À l'instar des professeurs, les bibliothécaires universitaires sont généralement tenus de s'engager dans des activités savantes, mais ils se retrouvent aussi de plus en plus dans une position où ils doivent guider les chercheurs et leur fournir des conseils sur les tendances émergentes de la communication savante. Cette présentation décrira comment la création d'une revue dirigée par des étudiants et qu'un cours sur la communication savante dans la faculté d'information et des études des médias de la Western University peuvent contribuer à répondre à ces besoins.
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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 | 0.056 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.008 | 0.018 |
| Scholarly communication | 0.030 | 0.020 |
| Open science | 0.005 | 0.027 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".