The potential influence of critical pedagogy on nursing praxis: Tools for disrupting stigma and discrimination within the profession
Bibliographic record
Abstract
Nursing work centers around attending to a person's health during many of life's most vulnerable moments, from birth to death. Given the high-stakes nature of this work, it is essential for nurses to critically reflect on their individual and collective impact, which can range from healing to harmful. The purpose of this paper is to use a philosophical inquiry approach and a critical lens to explore the potential influence of critical pedagogy (how we learn what we learn) on nursing praxis (why we do what we do) with the aim of disrupting stigma and discrimination within the profession. This paper draws on the works of Paulo Freire, Henry Giroux, and bell hooks to alert readers to particular windows of opportunity where an intentional adoption of critical pedagogy in nursing praxis may help the profession think differently about two important and related topics: relational violence and peer-led knowledge mobilization. As a practice-based and theoretically grounded profession, nurses often strive to bridge the theoretical with the practical and the individual with the systemic. Thus, developing a robust and philosophically rooted disciplinary body of knowledge is particularly important to help us defensibly grapple with the notions of truth and ethics that shape our work's very essence and impact.
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 | 0.039 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.009 | 0.063 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".