Bibliographic record
Abstract
Diversity is a broad yet powerful idea that encompasses the ideas of difference and complexity. Multiple forms of diversity are important in nursing and health care, yet it is often only “cultural” diversity that comes to mind and commands attention.As culture is often conflated with ethnicity, attention to cultural diversity often focuses narrowly and defines people by nation, ethnicity, or race. In contrast, this issue of the Journal offers a panoply of differences of concern to nursing. Diversity is of critical concern to Canadian society in general and Canadian health care and nursing in particular, because of our expressed commitment to justice and equity, especially in health care. Because inequities occur along the lines of difference — in relation to age, ability, income, ethnicity, sexual orientation, geography, and other forms of difference — attention to diversity is fundamental to a lessening of health inequities. Analyses of diversity and difference thus invariably lead to questions of equity — questions that are addressed skilfully in relation to health throughout the papers in this issue of the CJNR. Indeed, the importance of diversity, in all its forms, to health care, nursing practice, and nursing research is evidenced by the large number of submissions received for this issue and the range of concerns they addressed. To address equity, analyses of diversity must attend to language, power dynamics, the intersections among various forms of inequity, and the specific contexts within which inequities occur.The contributors to this issue of the Journal turn their attention to diversity with conscious analysis of how various forms of diversity and difference intersect, and how language, taken-for-granted ideas, and dominance operate to foster inequity based on difference. The papers included in this issue illustrate how language functions within the politics of difference and can serve to create and sustain inequity. Most importantly,Anderson offers a critique of a discourse that constructs “diversity” only in terms of categories of oppression such as CJNR 2004,Vol. 36 No 4,7–9
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".