Psychiatric education in North America
Bibliographic record
Abstract
In North America, the psychiatric workforce while relatively large, remains insufficient for the population needs. Specialist training opportunities in psychiatry continues to grow, reflected in both increased recruitment and competitiveness. Furthermore, the iterative process of curriculum development and standardisation of training encourages greater educational consistency. There is an ongoing growth in subspecialty training opportunities, however access varies across centres and curriculum gaps remain. The diverse demographic characteristics and requirements of populations also play a role in educational needs, such as youth mental health, tele-psychiatry, cultural, rural and addictions psychiatry. Advances in science such as genetics, and the use of technologies and digital media also invite innovative approaches to knowledge acquisition. Overall, training needs to be matched by sufficient numbers of experienced and skilful trainers, mentorship and leadership in psychiatry with awareness of physician wellbeing and the risks of burnout. In the USA and Canada, the growing prospect of fellowships in leadership and administration lay important foundations for the growth of psychiatry, driven by high quality education for the mental health professionals and leaders of tomorrow.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".