Predictors of Performance of Students from the Canadian Memorial Chiropractic College on the Licensure Examinations of the Canadian Chiropractic Examining Board
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to determine if the Canadian Memorial Chiropractic College (CMCC) structured admissions interview and other student measures predict success on the Canadian Chiropractic Examining Board (CCEB) examinations. METHODS: An independent researcher combined CMCC and CCEB data by student name and then anonymized the data and destroyed the linking information. Backward stepwise multiple linear regressions were applied to external dependent variables from the CCEB and internal independent variables from the CMCC. RESULTS: Forty percent of the variance in the basic science examination (R2 = 0.405) was explained by the independent variables of third year objective structured clinical examination practical and second-year grade point average (chi rhoGPA). Forty-five percent of the variance in the applied science examination (R2 = 0.448) was explained by the fourth year final examination and chi rhoGPA for years 4, 2, and 3. Twenty-four percent of the variance in the clinical decision making examination (R2 = 0.239) was explained by chi rhoGPAs of years 4, 1, 2, and 3. Sixteen percent of the variance in the clinical skills examination (R2 = 0.160) was explained by the third year objective structured clinical examination theory and chi rhoGPA for year 2. CONCLUSION: For this educational institution, the admissions interview is not a predictor of success on the outcome measures of the CCEB. Student chi rhoGPA in year 2 is critical to success on CCEB licensure examinations. This information infers that students should only continue in their education after they have demonstrated a mastery level at the end of year 2.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".