Using practice analysis to improve the certifying examinations for PAs
Bibliographic record
Abstract
A practice analysis is a tool that bridges knowledge and clinical performance into a format that permits assessment. For physician assistants (PAs), this contributes to a psychometrically sound examination administered by the National Commission on Certification of Physician Assistants (NCCPA). The 2004 practice analysis of 5,282 completed PA surveys (13.4% out of 39,517 sent) was representative of the PA population in years experience, geographical distribution, and practice specialty. The survey revealed 8 content domains with formulating the most likely diagnosis, basic science concepts, and pharmaceutical therapeutics as the three skills needed for most scenarios. The data were also analyzed by patient acuity (acute limited, chronic progressive, life-threatening emergency). As a result, NCCPA's test item pool and content blueprint for assessing core knowledge of American PAs on the Physician Assistant National Certifying Examination (PANCE) and the Physician Assistant National Recertifying Examination (PANRE) has been enhanced.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".