Critical Care Trainees’ Career Goals and Needs: A Canadian Survey
Bibliographic record
Abstract
BACKGROUND: For training programs to meet the needs of trainees, an understanding of their career goals and expectations is required. OBJECTIVES: Canadian critical care medicine (CCM) trainees were surveyed to understand their career goals in terms of clinical work, research, teaching, administration and management; and to identify their perceptions regarding the support they need to achieve their goals. METHODS: The online survey was sent to all trainees registered in a Canadian adult or pediatric CCM program. It documented the participants' demographics; their career expectations; the perceived barriers and enablers to achieve their career goals; and their perceptions relating to their chances of developing a career in different areas. RESULTS: A response rate of 85% (66 of 78) was obtained. The majority expected to work in an academic centre. Only approximately one-third (31%) estimated their chances of obtaining a position in CCM as >75%. The majority planned to devote 25% to 75% of their time performing clinical work and <25% in education, research or administration. The trainees perceived that there were limited employment opportunities. Networking and having specialized expertise were mentioned as being facilitators for obtaining employment. They expressed a need for more protected time, resources and mentorship for nonclinical tasks during training. CONCLUSION: CCM trainees perceived having only limited support to help them to achieve their career goals and anticipate difficulties in obtaining successful employment. They identified several gaps that could be addressed by training programs, including more mentoring in the areas of research, education and administration.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".