Interdisciplinary Training For Future Leaders Through The Create-Redevelop Graduate Student Program
Bibliographic record
Abstract
REDEVELOP is a graduate student training program funded by the NSERC-CREATE grant, starting in 2017. Its goal is to support the training of new professionals and researchers (> 100) who will be the next generation of science and engineering leaders and policymakers in Canada. The program has successfully developed a framework for operating almost completely virtually, well ahead of the world's transition to online learning due to the COVID-19 pandemic. Our psychology lab, The Individual and Team Performance (ITP) lab, has dedicated over a decade to researching and designing tools that enhance specific training and skill growth necessary for effective remote teamwork. In partnership with the REDEVELOP program, we support students in navigating the unique interpersonal and collaboration challenges posed by virtual team environments. We will discuss how a complex and multidisciplinary program succeeds in training graduate students to become stronger academics, practitioners, and communicators of knowledge.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.074 | 0.020 |
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".