PRICE-EARNINGS RATIO, DIVIDEND YIELD, AND MARKET-TO-BOOK RATIO TO PREDICT RETURN ON STOCK MARKET: EVIDENCE FROM THE EMERGING MARKETS
Bibliographic record
Abstract
<b><i>Objectives:</i></b> Evidence-based practice (EBP) is a clinical decision-making process combining the best available scientific evidence with clinician expertise and patient preference. While EBP has been associated with a range of benefits, it is recognized that EBP is used suboptimally by a range of health professionals, including naturopathic doctors (NDs). Canadian NDs have expressed a high level of interest in opportunities to improve their EBP skills; however, barriers exist, including those that apply broadly to health professionals, and those that are unique to the naturopathic profession. The objective of the present project was to co-design an EBP continuing education (CE) course tailored to the needs and preferences of Canadian NDs. <b><i>Design:</i></b> These needs were solicited through the use of focus groups. Groups were stratified based on participants' use of evidence at baseline. The focus groups asked NDs about their definition of EBP, and their interest in an EBP course, including preferred content, and method of delivery. The focus group discussions were transcribed, and thematic analysis was completed. <b><i>Subjects:</i></b> Twenty-two Canadian NDs participated. <b><i>Results:</i></b> Participants reported a high level of understanding of EBP, a high level of interest in participating in an EBP course and provided actionable recommendations about course content and delivery. Some of the themes that emerged were consistent across the groups while others differed by stratification. <b><i>Conclusions:</i></b> The findings of this project will inform the development and evaluation of a future CE course.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".