The application of the Functional Resonance Analysis Method (FRAM) to evaluate factors affecting times-to-completion and graduation in graduate studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The issue of attrition and graduation delays in higher education is almost as old as higher education itself. The impact of attrition on stu-dents, educational institutions, governments and economies is substantial. Despite the existence of many studies on attrition, the results fail to agree on what factors are actually relevant or primarily influential. To provide a new perspective on this issue, the Functional Resonance Analysis Method (FRAM) was applied to evaluate a case study in higher education. This approach enables the analyst to understand attrition as an outcome of the performance variability of students, supervisors and universities. The ap-plication of FRAM shows how the combination of functional variability (resonance) might cause or add up to the issues and how to identify sources of variability within the analyzed system.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| 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 it