Leaving the Nest: The Evolution of CHRPP (the Course of Human Participant Protection) | Quitter le nid : l’évolution du cours d’éthique sur la protection des participants humains
Bibliographic record
Abstract
Four years ago [Institution Name] University launched an online tutorial called CHRPP, the Course in Human Research Participant Protection, and published a paper based about its purpose, design, and usability in (Authors, 2009). CHRPP was originally created to raise awareness among research students about the federal policy regarding research ethics and to encourage ethical research practices. Self-assessments and interactive activities were built into the tutorial to help achieve our goals. Since the first publication CHRPP has been updated based on user feedback from a user satisfaction survey. The generally positive reception of this innovative tutorial led to it serving as the basis of a new national research ethics tutorial hosted by the Government of Canada’s Panel on Research Ethics. This paper summarizes the evolution of CHRPP from a homegrown solution for [Institution Name] University to an essential piece of Canada’s national research ethics education program. En 2008, l’Université Queen’s a lancé un tutoriel en ligne nommé CHRPP (Course in Human Research Participant Protection, cours sur la protection des participants humains à la recherche) et publié un article sur son objectif, sa conception et sa convivialité dans Balkwill, Stevenson, Stockley et Marlin (2009). Le CHRPP a été créé pour sensibiliser les étudiants qui font de la recherche sur la politique fédérale relative à l’éthique de recherche et pour favoriser les pratiques éthiques de recherche. Des autoévaluations et des activités interactives ont été intégrées au tutoriel pour nous aider à atteindre nos objectifs. Depuis sa première publication, le CHRPP a été mis à jour en se basant sur la rétroaction tirée d’une enquête sur la satisfaction des utilisateurs. La réception généralement positive qu’a reçue ce tutoriel innovateur lui a valu de servir de base pour un nouveau tutoriel national en éthique de la recherche qu’héberge le Groupe consultatif en éthique de la recherche du gouvernement du Canada. Cet article résume l’évolution du CHRPP qui, d’une solution maison pour un établissement est devenu une partie essentielle du programme national canadien d’éducation en éthique de la recherche.
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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 | 0.057 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.025 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".