Factors Predictive of Postgraduate Residency Placement: A Systematic Review
Bibliographic record
Abstract
This systematic review aimed to identify pharmacy student and school characteristics that are associated with higher postgraduate residency placement. Studies had to be an observational or experimental investigation, analyze pharmacy students and/or pharmacy schools, and report the statistical association, correlation, MV regression, propensity score analysis or matched analysis between a student or school variable with match success. Only studies that utilized multivariate analyses were included. The NewsCastle-Ottawa Quality Assessment Form for Cohort studies was used to assess risk of bias in the included studies. Student and school-level factors were then collected and synthesized via full text review. In total, there were 11 included studies. This review was limited by the observational design of the individual studies, the high likelihood of confounding factors, the types and frequency of characteristics explored, and the limited number of pharmacy students and schools analyzed by the included studies. In this study, it was found that the student characteristic of higher GPA, and the pharmacy school characteristics of higher NAPLEX pass rates, public funding, and a curricular program length over three years were associated with higher match rates.
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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 | 0.008 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".