Reflecting, Refueling, and Reframing: A 10-Year Retrospective Model for Faculty Development and Its Implications for Nursing Scholarship
Bibliographic record
Abstract
In this article, the authors retrace their journey during the past 10 years as faculty members engaged in the implementation of a new bachelor of nursing (collaborative) program. They outline the major personal challenges related to increasing credentials and portfolio development for teachers within a university environment. The authors extrapolate from the relevant literature on teaching and scholarship, and thereby analyze the methodologies that enhanced the faculty development process for them during this time. Specifically, they discuss the methods that facilitated meaningful reflection on their new roles and responsibilities; nurtured their professional growth and afforded opportunities for refueling and reenergizing along the way; and provided a vision for reframing their practice as nurse educators in light of previous experiences. With reference to Boyer's model of scholarship, the authors also explore possible implications for further analysis of the faculty development process within the broader context of nursing scholarship.
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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 | 0.050 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".