Self-Deception in Clinical Nursing Practice: A Concept Analysis
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we explore the phenomenon of "self-deception" within the context of nursing, focusing on how nurses employ this coping mechanism when faced with dissonance, distress, and conflicting situations in clinical settings. Our primary objective is to examine the phenomenon of self-deception using Rodgers' evolutionary method of concept analysis. Focusing on nurses' experiences in challenging situations, our analysis highlights how self-deception is often employed as a coping strategy. According to our conceptual analysis, self-deception in nursing clinical practice highlights tensions between different paradigms and expectations in healthcare settings. These tensions stem from the power dynamics and subservience that nurses often face, which can hinder their ability to advocate for themselves, their patients, and the nursing profession.
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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 | 0.199 | 0.380 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.009 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.033 |
| Insufficient payload (model declined to judge) | 0.001 | 0.006 |
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 it