The Marketed Image of Nursing to Prospective Students of Canadian Baccalaureate Nursing Programs
Bibliographic record
Abstract
This qualitative descriptive study examined and compared the online marketing materials of 91 baccalaureate nursing programs in Canada. It explored the prevalent physical and affective characteristics of nursing as marketed to prospective nursing students in five different regions of Canada (Eastern, Northern, Central, Prairie, and Western). The study examined Canadian nursing program websites for their emphasis on (1) descriptions of the symbos, roles and goals of nursing; (2) the character, characteristics and qualifications of nurses; (3) the human populations and physical environments wherein nurses work; (4) the bahaviours and work of nurses; (5) the selection criteria of nursing students; (6) approaches to nursing education, including the foci of curriculum; and (7) representations of commitment by nursing students and professional nurses. The study found that the Canadian image of nursing as marketed on baccalaureate websites varies according to region, with marked differences noted between online marketing materials of Francophone and anglophone program websites. The study findings raise questions about the "honesty" (congruence) of marketing images, and highlight the lack of "commitment" and "persistence" as attitudes and behaviours necessary for nursing practice in Canada. This study has implications for prospective students of nursing, nursing educators, nursing program developers, nursing recruiters, and governing nursing organizations and associations.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".