A comparison of research utilization among nurses working in Canadian civilian and United States Army healthcare settings
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
Researchers and theorists working in the field of knowledge translation point to the importance of organizational context in influencing research utilization. The study purpose was to compare research utilization in two different healthcare contexts--Canadian civilian and United States (US) Army settings. Contrary to the investigators' expectations, research utilization scores were lower in US Army settings, after controlling for potential predictors. In-service attendance, library access, belief suspension, gender, and years of experience interacted significantly with the setting (military or civilian) for research utilization. Predictors of research utilization common to both settings were attitude and belief suspension. Predictors in the US Army setting were trust and years of experience, and in the Canadian civilian setting were in-service attendance, time (organizational), research champion, and library access. While context is of central importance, individual and organizational predictors interact with context in important although not well-understood ways, and should not be ignored.
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 | 0.068 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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