Bibliographic record
Abstract
As ‘designerly’ ways of thinking and knowing are increasingly understood to be relevant in fields outside the traditional design disciplines, there is need to conceive of and design appropriate pedagogy. The challenge is to successfully negotiate disciplinary crossings in ways that simultaneously respect the discipline of design and provide a space for exploration and innovation, while at the same time produce results that satisfy individual disciplinary standards as well as the institutional standards of the university. The paper presents a case study of a novel graduate course in design research in the University of Toronto’s Knowledge Media Design Institute (KMDI) – a multidisciplinary community in which the design has been largely grounded in models from human- computer interaction (HCI). The model of pedagogy that emerged out of this experience and reflection is then situated in terms of prior work on interdisciplinary pedagogy. We propose that our model of pedagogy grounded in what we call disciplined transdisciplinarity has the potential to generalise to other settings.
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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".