Inter-Trans-Post Disciplinarity: Design Education in the Post-Industrial Era
Bibliographic record
Abstract
Design appears to be a young academic field without a clear and defined domain, when it is compared to other disciplines which are historically stabilized and acquired a better recognized disciplinary theoretical apparatus. Design thinking has grown often touching far territories of knowledge and always placing its line of research on the track of innovation, between material and immaterial, product and service. \nAs Design turns out to produce knowledge, while giving an interpretation to reality and being strategic for innovation, the following paper raises some questions: is Design a discipline without any given field? If we consider it as an open structure, what geometric organization is drawing while connecting other fields? Along with the occurrence of the post-industrial society of knowledge, should we still call the discipline industrial design? What are its epistemological assumptions? \nFrom a didactic and research experience at Carleton University in Ottawa (Canada) with the development of a Master of Interdisciplinary Design, the paper is a theoretical contribution through an interdisciplinary net of references, to witness the accomplishment of design as an academic discipline while sketching its complex character in contemporary post-industrial societies. Far from reductionism, the research pursues a conception of knowledge as a non-hierarchical social construct, developed in an interactive collaborative process.
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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.024 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".