Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Although central to educational decision-making, value in nursing education is rarely defined. As programs evolve through curricular reform, competency-based design, simulation, artificial intelligence, and digital learning, what makes these efforts genuinely valuable remains unclear. PURPOSE: This paper introduces the REFLECT Framework, a reflective conceptual model for guiding value-based decisions in nursing education. METHODS: Using an integrative analysis of literature from healthcare, education, and implementation science, value is conceptualized as a multidimensional construct encompassing seven dimensions: purpose alignment, evidence-informed pedagogy, pedagogical expertise, learner-centeredness, resource stewardship, equity, and contextual fit and sustainability. DISCUSSION: These dimensions support reflection on whether educational initiatives are effective, ethical, equitable, feasible, and aligned with nursing's professional and societal purposes. The framework can be applied at micro (course), meso (program), and macro (system) levels to guide deliberation about what matters, for whom, and under what conditions. CONCLUSION: The REFLECT Framework offers a structured, context-sensitive approach for advancing a deliberate and sustainable approach to shaping nursing education.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it