Hindsight Is 2020: A Graduate Student Perspective
Bibliographic record
Abstract
(Villeneuve and MacDonald 2006), from a graduate student perspective. In this 2006 report, the authors presented a series of predictions for the preferred future of nursing in Canada in 2020. Even without the pandemic, the pre-existing trends in healthcare and nursing did not favour success for the visions presented in this national nursing report. Now, two years after 2020, we examine the extent to which these predictions held true in the following areas: health systems, nursing practice, nursing workforce, nursing education and nursing regulation. We conclude that most of the preferred scenarios were unmet or partially met, and argue that it is critical to enact relevant preferred scenarios now. While the deleterious effects of the pandemic will be felt by the nursing profession for years, these experiences did not hinder our collective ability to lead change in Canada. We offer insights to provide recommendations for nursing actions toward a healthier future for Canadians. The best of nursing in Canada is within sight.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.027 | 0.022 |
| Scholarly communication | 0.020 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.007 | 0.018 |
| Insufficient payload (model declined to judge) | 0.013 | 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".