Achieving government, community and institutional goals through the measurement of performance: accountability and performance indicators in Ontario colleges and universities
Bibliographic record
Abstract
In 1998, the Ontario government established performance indicators for its publicly funded colleges and universities to both assess performance and distribute part of the public funds allocated to higher education. This initiative was consistent with the actions of governments throughout the world and has significance for both the systems of higher education and the individual institutions wherever it is in place. This study examined several issues including government motivation for measuring the performance of postsecondary institutions; a critical analysis of the Ontario accountability framework against both public policy goals for postsecondary education and established standards and criteria for performance measurement systems; perceptions of stakeholders regarding public goals and the efficacy of the current accountability system; and recommendations for changes to the Ontario performance indicator system based on research results. The study found that the perceptions of stakeholders regarding government goals for postsecondary education were reasonably consistent with those found in public documents. However, the lack of a clear statement of government goals, together with some misalignment of perceived goals and those the current performance indicators appear to be measuring, caused confusion and could also result in inappropriate steering effects on the behaviour of colleges and universities. The study also found that the current Ontario accountability framework was only moderately consistent with the standards and criteria for postsecondary performance indicators established in the literature. Other significant findings of the study include differences in perceived goals for colleges and universities but similar indicators to measure performance, the lack of provision for mission-related institutional goals contrary to recommendations in the literature, and that transferability from college to university, a clearly stated goal of the government, is neither measured nor rewarded by performance funding. The study relied on a review of government documents and related literature, and the results of a survey of stakeholders regarding government goals for postsecondary education, the relevance and reliability of the current performance indicators for measuring performance and influencing funding, and identification of other indicators relevant to assess the performance of Ontario colleges and universities. Recommendations for changes to the system and suggestions for future research are included.
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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 | 0.015 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".