The association of standardized patient educators (ASPE) gynecological teaching associate (GTA) and male urogenital teaching associate (MUTA) standards of best practice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Gynecological Teaching Associates (GTAs) and Male Urogenital Teaching Associates (MUTAs) instruct healthcare professional learners to perform accurate and respectful breast, speculum, bimanual vaginal, rectal, urogenital, and prostate examinations. During such sessions, the GTA/MUTA uses their own body to instruct while providing real-time feedback. While GTAs/MUTAs fall under the broader umbrella of Standardized Patient methodology, the specificity of their role indicates need for establishment of Standards of Best Practice (SOBP) for GTA/MUTA programs. On behalf of the Association of Standardized Patient Educators (ASPE), the Delphi process was utilized to reach international consensus identifying the Practices that comprise the ASPE GTA/MUTA SOBP. The original ASPE SOBP was used as the foundation for the iterative series of three surveys. Results were presented at the ASPE 2019 conference for additional feedback. Fifteen participants from four countries completed the Delphi process. Four of the original ASPE SOBP Domains were validated for GTA/MUTA programs: Safe Work Environment, Instructional Session Development, Training GTAs/MUTAs, and Program Management. Principles and Practices were shaped, and in some instances created, to best fit the distinct needs of GTA/MUTA programs. The ASPE GTA/MUTA SOBP apply to programs that engage GTAs/MUTAs in formative instructional sessions with learners. Programs that incorporate GTAs/MUTAs in simulation roles or in summative assessment are encouraged to reference the ASPE SOBP in conjunction with this document. The SOBP are aspirational and should be used to shape Practices within the program's local context. The ASPE GTA/MUTA SOBP will continue to evolve as our knowledge-base and practice develop.
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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 | 0.012 | 0.068 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it