Bibliographic record
Abstract
This issue of JANThis issue begins with three papers under the category heading Issues and innovations in nursing education.First, a paper from the United States of America (USA) presents an important critique of contemporary approaches to cultural education in nursing.The author argues that despite careful and rigorous curricular attention to culture, nursing students are currently taught about cultures as monoliths, and are expected to learn the alleged unique, distinguishing characteristics of each.She gives good reasons why this approach should be challenged, not least the impact of globalization in producing so many multicultural societies where there is a failure to care adequately for members of those groups who differ from the dominant culture.Theoretically, it is the anthropological notion of the other that is challenged with great erudition in this article and which, on reading, I felt presented nurse educators with a paradigm shift for teaching practice.For those who wish to pursue this subject further theoretically, and in a non-nursing context, I would recommend an article on anthropology, culture and the cinema that appeared coincidentally just as this important paper was undergoing editorial revision (Henley 2001).The second education paper reports on a study of self-directed learning (SDL).Groups of both teachers and students from eight United Kingdom (UK) paediatric intensive care nursing (ICU) courses identi®ed SDL as one method to be used alongside others, and related SDL to observable events rather than to cognitive processes.The author concludes that issues of control and autonomy within the learning environment need further exploration if the concept of SDL is to be advanced.It seems that at present, the cognitive goals of SDL are not well understood, at least in UK paediatric ICU nursing.The third article in this section concerns undergraduate students' perceptions of clin-
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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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.019 | 0.007 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.093 | 0.049 |
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".