Perceived images and expected roles of Indonesian nurses
Bibliographic record
Abstract
Abstract Aim The aim of this study was to explore how non‐nurses and nurses differ regarding the perceived images and expected roles of Indonesian nurses. Design A cross‐sectional survey study Methods An online tool shared via email was used to collect data in March 2014, from a convenient sample of 1,228 employees of a private university located in Karawaci, Indonesia. An English/Indonesian version of the survey was developed: 19 perception items and 19 expectation items using a 5‐point Likert scale. Independent sample t tests were used to compare groups. Results One hundred and forty‐three people completed the survey; a response rate of 11.6%. Thirteen were nurses and 130 were non‐nurses. Compared with nurses, non‐nurses were less likely to agree with statements that Indonesian nurses are self‐sacrificing, provide help to others, are devoted to caring, perform housekeeping duties and are knowledgeable. Monitoring nurses' image on a regular basis is essential. A public education campaign could focus on selected positive characteristics to improve the image of Indonesian nurses.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".