Re-thinking the Concept of Cultural Competency in Nursing Care of Older Adults
Bibliographic record
Abstract
The influx of migrants to Canada has resulted in a shift in the country's demographic landscape. Individuals often interpret and approach health and wellness through the lens of their cultural heritage, which has led to stereotyping behaviors and discriminatory practices, exacerbating the notion of "Othering". Immigrant older adults are likely to experience discrimination in a more dreadful way in the form of societal isolation and marginalization due to the collective systems of power such as ageism, ableism, and racism. This paper results from continuous thought-provoking discussions initiated by the first author (AM) in her doctoral program at the University of Western Ontario for the Philosophy of Nursing Science course, taught and facilitated by the second author (SM). After studying the course materials on "revolutionary science" and reflection on the process of paradigm shift introduced by Thomas Khun and engaging in critical discussions on a range of relevant philosophical concepts such as bio-power, othering, silencing and ignorance, marginalization, oppression, neoliberalism, health equity, and social justice, we have been prompted to rethink the concept of cultural competence in nursing education and healthcare practices, particularly in the context of nursing care of older adults. Therefore, in this paper, we will critique the concept of cultural competency in the context of an anti-racist and anti-oppressive lens and suggest a pivotal response to move towards an inquiry-driven approach based on cultural humility and respect in the nursing care of older adults.
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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 | 0.017 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.076 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.001 | 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".