Crossing Boundaries: The Design of an Interdisciplinary Training Program to Improve Care for the Frail Elderly
Bibliographic record
Abstract
The Technology Evaluation in the Elderly Network (TVN) was funded in July 2012 under the Canadian Networks of Centres of Excellence program. This article highlights the development and preliminary evaluation of the TVN Interdisciplinary Training Program. This program is based on an experiential learning approach that crosses a multitude of disciplines including health sciences, law, social sciences, and ethical aspects of working with the frail elderly. Opportunities within the program include mentorship, interdisciplinary online collaborative projects, external placements, academic products, pre-grant submission, trainee-driven requirements, Network meetings, online modules/webinars, and most importantly active involvement with patients, families, and their support systems. The authors have 120 trainees from approximately 23 different disciplines including law, ethics, public policy, social work, and engineering engaged in the program. Based on our evaluation this program has been perceived as highly valuable by the participants and the community.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".