Editorial perspective on “The Raison d'Être of Mutual Recognition: An Analysis of the 2015 Reforms to Research Ethics Review Policies, Processes and Problems in Québec”
Bibliographic record
Abstract
The reform of ethics reviews for large, multi-centre, research projects in health (clinical trials, genomics, health services research, epidemiology) does not affect the delivery, funding, or financing of health care services directly. It could therefore be said to be outside the scope of a journal documenting, analyzing, and comparing reforms taking place in the health care system. However, changing the rules according to which health research is conducted affects a small but influential group of stakeholders in health care decision-making, including health care professionals, health services analysts and academic health researchers involved in large collaborative empirical projects. It also affects patients enrolled in the research, again, a small but potentially important group of patients, those patients who can benefit from cutting edge research. Last, changing the environment in which health research operates in a jurisdiction is expected to have an effect on the diffusion of innovation in that jurisdiction’s health care system. We acknowledge that such a relationship is not easy to establish empirically, but it is certainly the case that governments investing in research in health hope to make their health care system (through their health care professionals and health services analysts, but also the general public) more receptive to and adept at adopting innovations in the field of health care. In that sense, we believe that reforms of the conditions under which health research is conducted falls within the scope of this journal. As usual, we invite our readers to weigh in and discuss that statement, as well as the content of this Health Reform Analysis. Michel Grignon, 5 November 2017. Réformer le protocole de revue éthique des grands projets de recherche multi-centriques en santé (essais cliniques, génomique, recherche en services de santé, épidémiologie) n’affecte pas la délivrance, le paiement ou le financement des soins directement. À ce titre, une telle réforme pourrait être considérée hors du champ d’un journal de documentation, d’analyse et de comparaison des reformes du système de santé. Pourtant, changer les règles selon lesquelles la recherche en santé est conduite affecte un groupe restreint mais influent de professionnels de la santé et d’analystes des services de santé, à savoir les universitaires impliqués dans les projets empiriques d’envergure; cela affecte aussi un groupe, là encore restreint mais potentiellement important, de patients, ceux pouvant bénéficier de la recherche de pointe. Enfin, en changeant l’environnement dans lequel se déroule la recherche en santé dans leur ressort administratif, les gouvernements espèrent influencer la diffusion de l’innovation dans leur système de santé. Bien sûr, une telle relation de cause à effet est difficile à établir empiriquement, mais il est certain que les gouvernements qui investissent dans la recherche en santé espèrent rendre leur système de santé (à travers les professionnels et les analystes des services de santé, mais aussi le grand public) plus réceptif, et plus apte à adopter les innovations dans le domaine de la santé. C’est en ce sens que nous pensons que les réformes des conditions dans lesquelles se pratique la recherche en santé entre dans le champ de ce journal. Comme d’habitude, nous invitons nos lecteurs à contribuer à cette discussion, ainsi qu’à commenter le contenu de cette Analyse de Réforme de Santé. Michel Grignon, 5 novembre 2017.
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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 | 0.037 | 0.102 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.013 | 0.015 |
| Scholarly communication | 0.024 | 0.006 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.038 | 0.031 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".