Nurse Faculty Experience with Research at a Polytechnic: A Qualitative Study
Bibliographic record
Abstract
There is increasing pressure to engage in research within the polytechnic and college sector, which is a role not historical to the setting (Roberts & Glod, 2013). There is little literature that applies to polytechnic and college faculty as it pertains to engaging in research. The purpose of this qualitative study was to understand the lived experiences of nurse faculty at a polytechnic, and the barriers and facilitating factors they experienced as they engaged in a large research project. Seven faculty members participated in total. Five of the seven faculty members participated in two different focus groups, and the remaining two faculty members participated in individual interviews. Faculty were recruited from those who had recently participated in a large, collaborative research project at the institution. The participants experienced being a learner, being part of a community of practice, experiencing frustration, and needing more support in their ability to complete the research project. These fndings are supported by the literature related to university faculty engaging in research. Recommendations for facilitating faculty’s engagement in research include providing access to a variety of library databases, professional development opportunities, and institutional supports.
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.
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 | 0.019 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.011 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".