Health Professional Student Placements and Workforce Location Outcomes: Protocol of an Observational Cohort Study
Bibliographic record
Abstract
BACKGROUND: The successful recruitment and retention of health professionals to rural and remote areas of Australia is a health policy priority. Nursing or allied health professional students' learning placements in the Northern Territory (NT) of Australia, most of which is considered remote, may influence rural or remote work location decisions. OBJECTIVE: The aim of this study is to determine where allied health professionals and nurses who have had a student placement in the NT of Australia end up practicing. METHODS: This research is an observational cohort study, with data collection occurring at baseline and then repeated annually over 10 years (ie, 2017-2018 to 2029). The baseline data collection includes a demographic profile of allied health and nursing students and their evaluations of their NT placements using a nationally consistent questionnaire (ie, the Student Satisfaction Survey). The Work Location Survey, which will be administered annually, will track work location and the influences on work location decisions. RESULTS: This study will generate unique data on the remote and rural work locations of nursing and allied health professional students who had a placement in the NT of Australia. It will be able to determine what are the most important characteristics of those who take up remote and rural employment, even if outside of the NT, and to identify barriers to remote employment. CONCLUSIONS: This study will add knowledge to the literature regarding rates of allied health and nursing professionals working in remote or rural settings following remote or rural learning placements. The results will be of interest to government and remote health workforce planners. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12620000797976; https://www.anzctr.org.au/ACTRN12620000797976.aspx. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/21832.
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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 | 0.058 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".