Perceptions of Academic Supports for Indigenous Nursing Students
Bibliographic record
Abstract
Given the education completion gap between Indigenous students and non-Indigenous students and the need for more Indigenous nurses, support for Indigenous nursing students is imperative for academic success. Indigenous nursing students face a number of barriers to success and struggle with the demands of the university setting. Academic, financial, personal, and cultural supports may assist students to successfully adapt and overcome these barriers. Educational institutions, such as Saskatchewan Polytechnic, have recognized barriers to Indigenous student success and have put a variety of measures in place to assist students. This paper aims to examine the current literature on Indigenous nursing student perception and academic support staff perception of available supports. The literature suggests that facilitative factors such as collaborative relationships between support services, individual supports, the learning environment, financial supports, and student characteristics all play a role in the academic success of students. Stressors, health, institutional racism, and feelings of shame and self-doubt are some barriers students must overcome. Within the larger context, students’ pre-university educational experience, the academic environment, and program characteristics impact the effectiveness of support services. Indigenous nursing students and Indigenous students from other programs share similar perceptions as to the effectiveness of support services. The perception of academic staff is that the needs of both Indigenous nursing and non-nursing students are similar. Although there is little research in the area of library services in relation to how they support Indigenous nursing student success, student perceptions of other support services are positive when students use them...
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 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".