Bibliographic record
Abstract
Purpose – The purpose of this paper is to discuss how the province over time has addressed problems that are generic to many jurisdictions in assuring quality: level of aggregation, pooling, definition of new and continuing programs, scope of jurisdiction, role of governors, performance indicators, relationship to accreditation, programs versus credentials, benchmarking and isomorphism. The paper will pay particular attention to the balance between institutional autonomy in promoting quality and innovation in contrast to system-wide standards for assuring quality. The Province of Ontario has had some form of quality assurance since 1969. For most of the period since then, there were separate forms for undergraduate and graduate programs. Eligibility for public funding is based on the assurance of quality by a buffer body. In 2010, after two years of work, a province-wide task force devised a new framework. Design/methodology/approach – The structure of the paper is a series of “problem/solution” discussions, for example, aggregation, pooling, isomorphism and jurisdiction. Findings – Some problems are generic, for example, how to define a “new” program. Assuring quality and enhancing quality are fundamentally different in terms of process. Research limitations/implications – Although many of the problems discussed are generic, the paper is based on the experience of one jurisdiction. Practical implications – The article will be useful in post-secondary systems seeking to balance autonomy and innovation with central accountability and standardization. It is particularly applicable to undifferentiated systems. Social implications – Implications for public policy are mainly about locating the most effective center of gravity between assuring quality and enhancing quality, and between promoting quality and ensuring accountability. Originality/value – The approach of the discussion and analysis is novel, and the results portable.
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.
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 | 0.016 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.030 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".