The Collaboration of Fine Art & Engineering at the University of Guelph
Bibliographic record
Abstract
Fine Art and Engineering view design as a central element, if not the central element, of their respective disciplines.Though engineers and artists offer mutually beneficial insights and expertise in design, these two disciplines routinely exist as separate entities in the development of design curriculum, and build facilities independently in the academic environment.The School of Fine Art and Music (SOFAM) and the School of Engineering (SOE) at the University of Guelph have increased their collaboration over the last few years.The relationship started with the provision of engineering advice to guide the creation of two large sculptures then progressed to team teaching of a fourth year elective course as the next element in the partnership.The SOE is currently undergoing a significant expansion.This growth has initiated plans for shared resources and facilities that will support advanced design and fabrication capabilities for engineers and artists alike.Collaboration will promote a cross fertilization of ideas between faculty and students through such initiatives as shared courses and design studios that will combine students from both departments.Successful cross-disciplinary collaboration offers the opportunity for SOFAM and SOE students to be leaders in creative, innovative, and sustainable design.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.071 | 0.008 |
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".