Global Rating Scale for the Assessment of Paramedic Clinical Competence
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to develop and critically appraise a global rating scale (GRS) for the assessment of individual paramedic clinical competence at the entry-to-practice level. METHODS: The development phase of this study involved task analysis by experts, contributions from a focus group, and a modified Delphi process using a national expert panel to establish evidence of content validity. The critical appraisal phase had two raters apply the GRS, developed in the first phase, to a series of sample performances from three groups: novice paramedic students (group 1), paramedic students at the entry-to-practice level (group 2), and experienced paramedics (group 3). Using data from this process, we examined the tool's reliability within each group and tested the discriminative validity hypothesis that higher scores would be associated with higher levels of training and experience. RESULTS: The development phase resulted in a seven-dimension, seven-point adjectival GRS. The two independent blinded raters scored 81 recorded sample performances (n = 25 in group 1, n = 33 in group 2, n = 23 in group 3) using the GRS. For groups 1, 2, and 3, respectively, interrater reliability reached 0.75, 0.88, and 0.94. Intrarater reliability reached 0.94 and the internal consistency ranged from 0.53 to 0.89. Rater differences contributed 0-5.7% of the total variance. The GRS scores assigned to each group increased with level of experience, both using the overall rating (means = 2.3, 4.1, 5.0; p < 0.001) and considering each dimension separately. Applying a modified borderline group method, 54.9% of group 1, 13.4% of group 2, and 2.9% of group 3 were below the cut score. CONCLUSION: The results of this study provide evidence that the scores generated using this scale can be valid for the purpose of making decisions regarding paramedic clinical competence.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".