Reimagining the 4M Framework in Educational Development for SoTL
Bibliographic record
Abstract
In this paper, we seek to contextualize our work in SoTL-focused educational development and those who work to support others in SoTL, as interstitially spaced across the 4M Framework, re-envisioned as a flexible but formalized professional continua. The establishment of a model for educational development SoTL-related activity allows for the opportunity to explore how this work is done in a systematic manner. We offer our ideas and visions through, what we term, the 4M Continua for Educational Development as a possible understanding of the work that SoTL-focused educational developers do, as well as those who engage in educational development more broadly. While the 4M Framework provides a guide through four interrelated organizational lenses: micro; meso; macro; and mega, we have adapted a model to situate educational development work using the 4M Framework to inform the ways in which we do, contribute to, consume, advocate, and support SoTL broadly, including at local, provincial, national, and international levels. The 4M Continua can be an avenue for those who do educational development to describe their work, where the work is situated, and how support can be offered throughout the community.
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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 | 0.024 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.007 | 0.043 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.005 | 0.008 |
| 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".