Transforming Academic Internationalization in Nursing Education in Ghana
Bibliographic record
Abstract
The development of formal nursing education in Ghana has been influenced by international organizations since its beginning in the mid-1940s. Some of the 218 accredited nursing institutions in Ghana engage in academic internationalization through several international activities. Today, the focus of nursing education and health care delivery worldwide appears to be shifting towards globalization owing to the emerging market economies and political alliances that lean towards neoliberal perspectives. In this paper, the aspects of internationalization and globalization of Ghanaian nursing education that need to be retained and those aspects that require transformation are discussed. International student exchange programs with a Western Canadian university and the introduction of French and sign languages into nursing programs were identified as internationalization efforts in Ghanaian nursing education that should be promoted. The need for a policy review regarding a Ghanaian university’s international activities with the Canadian university is proposed to ensure equal benefits for students from the collaborating schools. This paper calls for a revision in the Ghanaian university nursing curriculum to integrate courses on global and immigrant health, interdisciplinary education, and team-centric leadership preparation to enhance undergraduate nurses with global working skills.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".