Interior Design at a Crossroads: Embracing Specificity through Process, Research, and Knowledge
Bibliographic record
Abstract
Tiiu Poldma is Vice Dean of Graduate Studies and Research in the Faculty of Environmental Design, and associate professor at the School of Industrial Design at the University of Montreal. Tiiu Poldma received a BID at Ryerson in 1982 (Toronto), MA in Culture and Values in Education in 1999 and Doctor of Philosophy in 2003, both from McGill University in Montreal, Canada. She teaches interior design studio and theory within the Bachelor of Interior Design program at the University of Montreal, and advanced research methodologies in the Masters of Science and Ph.D. programs at the Faculty of Environmental Design. She is currently the Director of the Research Group GRID(Group for Research in Illumination and Design) and heads up the Colour, Light and Form Lab (Laboratoire Forme*couleur*lumiere) at the faculty. She accredits design programs as a site evaluator for CIDAboth in Canada and the United States, and is also a member of the Editorial Board of Inderscience where she is the Regional Editor of the Journal of Design Research (JDR), and serves on the Editorial Board of Design/Science/Planning (Techne Press, Amsterdam).
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 | 0.023 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.008 | 0.082 |
| Scholarly communication | 0.029 | 0.025 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.004 | 0.005 |
| 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".