Bibliographic record
Abstract
This short paper outlines the design and development of a multi-phase, cross-institution Instructional Skills Workshop (ISW) program that was conceived by educational developers from five higher educational institutions in Halifax, Nova Scotia. The initiative is grounded in the belief that implementing the ISW program in the Halifax Regional Municipal (HRM) area will foster a local community of practice and further cross-institutional initiatives focused on enhancing teaching and learning approaches. This paper offers a brief historical background and rationale of the ISW program, and details of implementation. In addition, the lead coordinators share their reflections on the challenges and implications resulting from the process of adapting this established program to fit an innovative and mutually supportive cross-institutional design within the HRM. Ce court article présente la conception et l’élaboration d’Instructional Skills Workshop (ISW), un programme interétablissement en plusieurs phases qui a été conçu par des concepteurs pédagogiques provenant de cinq établissements d’enseignement supérieur d’Halifax, en Nouvelle-Écosse. L’initiative repose sur l’idée que la mise en œuvre d’ISW dans la municipalité régionale d’Halifax encouragera le développement d’une communauté de pratique et de projets interétablissements visant à améliorer les approches d’enseignement et d’apprentissage. Nous présentons brièvement l’histoire et les raisons au fondement de l’ISW ainsi que les détails de sa mise en œuvre. De plus, les coordonnateurs en chef réfléchissent aux difficultés et aux conséquences du processus d’adaptation de ce programme bien établi au concept interétablissement novateur et solidaire au sein de la municipalité régionale d’Halifax.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.602 | 0.408 |
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".