Assessing Quality in Postsecondary Education
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
For many years the benefits conferred by a higher education went undisputed. But students, employers, governments, and taxpayers are now demanding evidence of educational quality and value. At the same time, fiscally strapped governments are raising questions about how institutions are funded and the role quality should play in setting funding levels. In the face of these mounting pressures, jurisdictions around the world are working toward designing meaningful indicators to measure the performance of postsecondary institutions that go beyond enrolment numbers, graduation rates, and ever-popular reputational rankings. Assessing Quality in Postsecondary Education: International Perspectives presents a collection of thought-provoking essays by world-renowned higher-education thinkers and policy experts that discuss ways of defining and measuring academic quality. The papers were presented at a conference convened by the Higher Education Quality Council of Ontario in May 2017 and provide valuable insight into this pressing issue and underscore the need for reform.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 it