Health Science Education Graduate Program Handbook - 2019/2020
Bibliographic record
Abstract
We are pleased that you have selected our program to pursue your passion for education.The HSED program is designed primarily for active health professionals that wish to strengthen their abilities as educators in their area of expertise and to develop proficiency in various forms of scholarship.Although, it is also open to non-clinicians that aspire to be scholars in the field of health sciences education.In particular, the program provides students with opportunities to develop a comprehensive understanding of current professional practice in health science teaching and pedagogy as well as important research, innovation, and evaluation approaches in health science education.This handbook provides students with resources that will aid in successful completion of a Master's of Science degree in Health Sciences Education.Please note that this handbook is a compliment to the School of Graduate Studies Calendar.Be sure to also refer to the 'Resources' section of the School of Graduate Studies (SGS) website (https://graduate.mcmaster.ca/resources)as well as the School of Graduate Studies Calendar for the most up-to-date information regarding sessional dates, deadlines, enrollment information, and more.All SGS student-initiated forms can be found at this link.We wish you all the best during your time in the program!
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.564 | 0.476 |
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".