Local socioeconomic status and paramedic students' academic performance
Bibliographic record
Abstract
Research indicates that students of lower socioeconomic status are educationally disadvantaged. This study sought to examine differences in paramedic students' academic performance from counties with varied socioeconomic status in the United States of America. Student performance data and socioeconomic status data were combined for counties within the states of California, Mississippi, Louisiana, Texas and Virginia. Linear multiple regression modelling was performed to determine the relationship between income, high school graduation rate, poverty and food insecurity, with first-attempt scores on the Fisdap Paramedic Readiness Exam versions 3 and 4. Linear regression models indicated that there was a significant relationship between county-level income, poverty, graduation rate, food insecurity, and paramedic student academic performance. It remains unclear what type of relationship exists between individual socioeconomic status and individual academic performance of paramedic students. These findings support the future collection of individual student socioeconomic data to identify issues and mitigate impact on academic performance.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".