Moderating Effect of Age and Supervisory Status on Telework and Job Satisfaction Among Federal Employees
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
Peer feedback benefits nursing education and practice by fostering collegial relationships and promoting the quality of care, yet students often lack training to engage effectively. While existing research has examined student perspectives, the experiences and strategies employed by nursing faculty remain underexplored. The purpose of this qualitative study, guided by the student feedback literacy framework, was to explore the perspectives of nursing faculty on the barriers, opportunities, and strategies for developing peer feedback skills among undergraduate nursing students. Seventeen Canadian nursing faculty participated in semi-structured virtual interviews. Analysis revealed five themes that aligned with the study’s three foci: strategies (a) teaching strategies and structural support; (b) shaping peer feedback practices; (c) learning environment and relational dynamics; (d) role modelling and professional socialization; and (e) challenges and barriers to feedback engagement. Findings revealed that peer feedback development is a collaborative process, requiring students’ active engagement alongside faculty guidance. A structured and formally taught approach that is responsive to student diversity, fosters safe learning environments, and normalizes feedback through culture and role modelling was emphasized. Future research could examine the perspectives of new graduate nurses, who stand at the intersection of education and practice. Nursing students who gain confidence in giving and receiving peer feedback are better prepared for reflective practice, effective communication, and safe, independent clinical work and ultimately contributing to positive social change.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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