Examining the potential of nurse practitioners from a critical social justice perspective
Bibliographic record
Abstract
Nurse practitioners (NPs) are increasingly called on to provide high-quality health-care particularly for people who face significant barriers to accessing services. Although discourses of social justice have become relatively common in nursing and health services literature, critical analyses of how NP roles articulate with social justice issues have received less attention. In this study, we examine the role of NPs from a critical social justice perspective. A critical social justice lens raises morally significant questions, for example, why certain individuals and groups bear a disproportionate burden of illness and suffering; what social conditions contribute to disparities in health and social status; and what social mandate NPs ought to develop in response to these realities. In our analysis, we draw on lessons learned from the initial Canadian experience with the introduction of NPs in the 1970s to consider the renewed and burgeoning interest in NPs in Canada, Australia and elsewhere. As we argue, a critical social justice perspective (in addition to the biomedical foci of NP practice) will be essential to sustaining long-term, socially responsive NP roles and achieving greater equity in health and health-care.
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 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 | 0.014 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".