Bibliographic record
Abstract
This poster presents the opinions of twenty supervising physicians on how Manitoba’s 116 P.A.s contribute to Value and physician’s wellness. Design: In May 2019, seventy-two Manitoba physicians who supervise 116 PAs were sent a twenty-question electronic survey asking their perspectives of P.A. Value as a component of an on-going quality assurance program. A Literature review using the Neil John Maclean Health Sciences Library One-Stop, PubMed, and Google Scholar search engines used the terms Value, physician assistant, and combinations of phrases related to P.A. benefit, P.A. values, Physician Value, and Canadian physician concerns with P.A.s occurred to guide the question development. Results: Twenty physicians responded from the list of the seventy-two physician supervisors contacted, representing a response rate of 27.7%. Three of the physician respondents have employed a P.A. for less than a year, 85% or 16 M.D. for more than two years, with 36.84% of the total for longer than five years. Eighty-five percent (n=18/20) of the responding physicians rated the Value of having a P.A. as very valuable or extremely valuable while 95% (n=19) were likely or extremely likely to recommend hiring a P.A. to a friend or colleague. One physician did not find value in the P.A. they hired. The phrases used by physicians in describing the Value P.A.s brought to Manitoba Healthcare included Honesty and Respect (78.95%), Improved Access (73%), Excellence In Care (63.1%), A Better Workplace (78.95%), Better Patient Safety (73.68%), Better Teamwork (84.21%), Accountability (73.68%), Efficiency (73.68%), Decreased Stress 42.11%, and Better Communication with Patients (57.89%). CONCLUSION: Ultimately, the determination of P.A.'s Value is through the lenses of those looking and asking what is needed. Manitoba physicians represented in this survey indicate extreme satisfaction with the quality and Value P.A.s contribute to their practice environment and personal lives.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".