pathto Pedagogy University of Manitoba Centre for the Advancement of Teaching & Learning
Bibliographic record
Abstract
For the Centre, the following Values Statements underlie our practices: •\t Effective teaching and learning are key elements in the core business of The University of Manitoba. As such, the mandate and activities of the Centre must support the Strategic Planning Framework priorities, and the University’s current and future practices and policies. •\t Enhancing teaching is better accomplished through building communities of practice and partnerships rather than treatment or remediation. •\t Evidence and best-practice are the foundation of the Centre’s teaching, research, and services. •\t We commit to the growth of teachers and learners during their entire engagement with the University. •\t The Centre is an important part of the UM learning and teaching ecosystem. Optimizing teaching and learning involves a synergy between pedagogical and discipline expertise, and requires a genuine partnership between the Centre and our colleagues in other disciplines. To collaborate with faculty, academic units, graduate students, other instructors, and the University Community to build teaching and learning capacity, expertise and innovation, we have reflected on our available resources and proposed a significant transformation. The Centre received prioritized funding in 2013 to begin this transformation and I am pleased that we have now completed our initial recruitment, renewal, and redeployment plans.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.160 | 0.024 |
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".