Cohort Analysis and Reporting for Graduate Attribute Assessment
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 Graduate Attribute Information Analysis system (GAIA) was developed at the University of Ottawa to support data collection and performance management of graduate attributes for engineering programs at the program level and at the course level [10]. This paper reports on our research to develop support for cohort analysis and reporting by providing a single consistent view of graduate attributes (GA) and performance indicators for groups of students who started and finished an engineering program at the same time. This is supported by two special purpose reports: Graduate Attribute Report per Cohort (GAR/C) and Course Progression Report per Cohort (CPR/C). The former shows average GA data per attribute, the latter tracks student achievement as students progress in their program. It also adds to the historic data trend analysis for a program. Furthermore, a COOP Progress Report per cohort (COOPR/C) is generated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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