The quality of doctoral nursing education in South Africa
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The number of doctoral programmes in nursing has multiplied rapidly throughout the world. This has led to widespread concern about nursing doctoral education, specifically with regard to the quality of curricula and faculty, as well as to the availability of appropriate institutional resources. In South Africa, no study of these issues has been conducted at a national level. OBJECTIVE: To explore and describe the quality of nursing doctoral education in South Africa from the perspectives of deans, faculty, doctoral graduates and students. METHOD: A cross-sectional survey design was used. All deans (N = 15; n = 12), faculty (N = 50; n = 26), doctoral graduates (N = 43; n = 26) and students (N = 106; n = 63) at South African nursing schools that offer a nursing doctoral programme (N = 16; n = 15) were invited to participate. Data were collected by means of structured email-mediated Quality of Nursing Doctoral Education surveys. RESULTS: Overall, the graduate participants scored their programme quality most positively of all the groups and faculty scored it most negatively. All of the groups rated the quality of their doctoral programmes as good, but certain problems related to the quality of resources, students and faculty were identified. CONCLUSION: These evaluations, by the people directly involved in the programmes, demonstrated significant differences amongst the groups and thus provide valuable baseline data for building strategies to improve the quality of doctoral nursing education in South Africa.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it