A novel program for ABSN students to generate interest in geriatrics and geriatric nursing research
Bibliographic record
Abstract
The current shortage of nurse researchers in geriatrics adversely affects the capacity of nurses to conduct research to advance the evidence-based care of older adults. In an effort to generate interest in geriatrics and geriatric nursing research, the Duke University School of Nursing designed a summer internship for four students enrolled in the accelerated baccalaureate nursing (ABSN) program. This paper describes the experience of these ABSN students and the staff and faculty who worked with them. The program design, staff and faculty experiences, benefits and challenges, as well as recommendations for future programs are discussed. The purpose of this article is to highlight the benefits and challenges of offering research experiences to nursing students in an ABSN program to stimulate interest in geriatrics and geriatric nursing research.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".