CAREER PLANS OF GRADUATES OF A CANADIAN DENTAL SCHOOL: PRELIMINARY REPORT OF A 5-YEAR SURVEY.
Bibliographic record
Abstract
OBJECTIVE: Comprehensive data on the characteristics and opinions of graduating dental students in Canada are lacking. Specifically, only minimal information is available on graduates' immediate career plans and factors that may influence their decisions regarding these plans. Our aim was to gather such data to allow better understanding of this issue and improve the design of future studies on this topic. METHODS: The Career Development Committee at the school of dentistry, University of Alberta, designed a short survey to be administered to graduating students over 5 years to gain insight into their immediate career plans and opinions on career services at the school. Preliminary results from 2012-2014 are reported here. RESULTS: With a response rate of close to 90% (n = 99/111), the data reveal considerable differences in immediate career plans between the surveyed students and those in other schools in Canada and the United States. Of the students, 89% were planning to work in a general dental practice and only 9% were planning to enroll in advanced education, including general practice residency training. CONCLUSION: More research is needed to better understand the factors affecting career path decisions of 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".