Recruitment and outreach for a new multidisciplinary design program
Bibliographic record
Abstract
A new three-year Bachelor of Multidisciplinary Design – Experiential Learning at the University of Ottawa was approved by the Ontario Ministry of Colleges and Universities. It will welcome its first student cohort in the Fall of 2023. The flexible program combines engineering courses with other disciplines, such as social sciences or business, to provide students with the skills required for modern multidisciplinary job markets. Since this new program is not a traditional engineering discipline, recruitment efforts needed to be modified from those used elsewhere in the Faculty. The program is designed for students who have a diverse set of interests, and who are passionate about a topic adjacent to engineering that requires additional multidisciplinary skills, rather than those wanting to be engineers. Therefore, existing messaging and approaches were unlikely to appeal to targeted students. A range of strategies were used to recruit students to the program with varying degrees of effectiveness.
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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 | 0.017 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.010 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.040 | 0.010 |
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".