A philosophical analysis of anti‐intellectualism in nursing: Newman’s view of a university education
Bibliographic record
Abstract
Canadian and international nursing educators are increasingly concerned with the quality of university nursing education. Contemporary nursing education is fraught by a growing anti-intellectualism coupled with the dominance of neoliberalism and corporate university business culture. Amid these challenges, nursing schools must prepare nurses to provide care in an era compounded by social and health inequities. The purpose of this paper was to explore the philosophical and contextual factors influencing anti-intellectualism in nursing education. We use John Henry Newman's view of the purpose of a university education as a heuristic perspective to examine anti-intellectualism in nursing. We contend that the ideological worship of technological advances, a culture of consumerism, quality improvement and risk management, the primacy of doing over thinking, competency-based curricula and business models rooted in neoliberal financial policies reinforce anti-intellectualism in nursing. Anti-intellectualism is a complex issue to address within the corporate university culture. We propose multiple strategies at the disciplinary, university and sociopolitical levels to decrease anti-intellectualism. Counteracting anti-intellectualism requires critical thinking, praxis and emancipation. Nurses should critically examine this anti-intellectual trend as it limits the advancement of the discipline and marginalizes its contributions within the academy. If nurses do not address this challenge, the survival of nursing as an academic discipline may be jeopardized.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.059 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| 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".