Exploring Nursing Roles Across North American Borders
Bibliographic record
Abstract
Professional nurses are challenged by the increasing complexity of their own healthcare delivery systems and by the growing interconnectivity of healthcare systems worldwide. There are increasing calls for practice across boundaries; however, the role and scope of nursing practice within individual countries are often unclear, ill-defined, and misunderstood by nurses from other countries. In this collaborative educational project among six schools of nursing located in Canada, México, and the United States, nursing students and faculty are exploring the role of the nurse within each country's healthcare system while striving to develop their multicultural awareness. Participating faculty describe the process, challenges, and keys to success found in creating and living this international project. They share strategies for addressing challenges, which included meeting deadlines, time differences, differing academic schedules, writing joint documents in two languages, designing and presenting a shared course, and creating an exchange process between the six partner schools. They describe the evolution of their working relationships, the language challenges, and the joy of coming together as newfound colleagues and friends.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.007 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".