HEALTH CAREER PROMOTION IN THE NEW ENGLAND AREA OF NEW SOUTH WALES: A PROGRAM TO SUPPORT HIGH SCHOOL CAREER ADVISERS
Bibliographic record
Abstract
OBJECTIVE: To facilitate the area's high school careers advisers' ability to effectively promote health careers to students. DESIGN: Three cross sectional evaluation surveys at the end of each one-day workshop. SETTING: Conference rooms in three regional centres (Armidale, Moree and Tamworth, New South Wales). SUBJECTS: Twenty-two high school careers advisers. INTERVENTION: One-day workshop. MAIN OUTCOME MEASURES: High school careers advisers' self-rated assessment in terms of the effective delivery of appropriate information and opportunities to network. RESULTS: Participants agreed that the workshop conveyed relevant information (3.8), were of high standard (3.5) and enabled them to identify students wanting to pursue health careers (2.9). Networking between health professionals and career advisers was rated as the most beneficial aspect by a majority of participants (60%). The scenario was rated as a useful tool to educate advisers about health careers (3.8). CONCLUSION: Collaborative workshops between advisers and health professionals are useful in facilitating networks to promote health careers in high schools in rural areas. The use of a farm injury scenario as a learning tool was effective in educating advisers about health careers. WHAT IS ALREADY KNOWN: Previous research carried out in the USA6 and Australia demonstrated that high school careers advisers needed to target high school students earlier in their studies before senior subjects were decided and that about a quarter of careers advisers indicated poor knowledge about health careers.10 WHAT THIS STUDY ADDS: Provision of practical support to high school careers advisers, such as distributing a mentorship directory and up-to-date health career kits as well as facilitating networking with health professionals constitute effective means to promote health careers to high school students.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".