Bibliographic record
Abstract
Welcome and thank you very much Marnie for finding the time to speak to us today.This interview is for the special issue we are doing on the history of nursing education.Pauline and I [the co-editors of the special issue] thought it would be wonderful to discuss some of the really important developments in nursing education in Canada that quite a lot of our faculty and the members of the profession more generally might not have a sense of.In particular, the collaborative programs and the importance of collaborative programs in Canadian nursing education.We of course thought of you as one of the key people in the development of collaborative programs and in encouraging the collaborative programs to push forward the entry-to-practice at a baccalaureate level, and because the University of Alberta was a key player in this story, we would be really interested in your reflections on how this was accomplished, in bringing the hospital schools and the colleges all together around baccalaureate education.Dr. Wood: It started through our meeting together.I came to Alberta in 1987, and that was the same year that Heather Andrews was appointed as the director of the university hospital school of nursing and Irene Gataint was the head of nursing at Red Deer College then.The three of us stayed in our positions long enough to ensure that the collaborative effort happened, which was the largest ever seen in nursing education in Canada.So it takes us back a long way back to 1991, which is the year when the larger collaborative program was approved and started.Initial planning had begun a few years earlier, around 1985, when the people from Red Deer College, Irene Gataint and Shirley Chance, and Dr Janet Ross Kerr from the university D re Nelson : Bienvenue, Marnie, et merci beaucoup de prendre le temps de discuter avec nous aujourd'hui.Cette entrevue fera partie d'une édition spéciale portant sur l'histoire de la formation en sciences infirmières.Pauline et moi (coéditrices de l'édition spéciale) avons pensé qu'il serait fantastique d'aborder quelques-unes des très importantes avancées dans ce domaine au Canada, qui pourraient avoir échappé à l'attention d'un bon nombre de notre personnel enseignant et des membres de la profession en général.Je pense en particulier aux programmes de collaboration et de leur importance dans la formation en sciences infirmières au Canada.Nous avons alors pensé à vous, l'une des joueuses clés dans la création de ces programmes et dans leur défense, afin de faire du baccalauréat en sciences infirmières la norme pour accéder à la pratique.Et puisque la University of Alberta a joué un rôle essentiel dans l'histoire, nous aimerions vraiment avoir votre point de vue sur le parcours de cette réalisation, qui réunit les collèges et les écoles en milieu hospitalier autour de la formation au baccalauréat.D re Wood : Tout cela a commencé par une rencontre.Je suis arrivée en Alberta en 1987, l'année où Heather Andrews a été nommée directrice de l'école des sciences infirmières en milieu hospitalier et où Irene Gataint dirigeait le programme en sciences infirmières au Red Deer College.Nous avons toutes trois occupé nos postes assez longtemps pour aboutir à un effort de collaboration, le plus grand jamais vu en matière de formation en sciences infirmières au Canada.Ce qui nous amène à 1991, soit il y a bien longtemps, année de l'autorisation et du lancement du plus important programme de collaboration.La planification initiale avait été entamée
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.099 | 0.040 |
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".