Bibliographic record
Abstract
This paper provides an overview of the higher education sector in Canada, so it can serve as a comparison to that in Australia. It seeks to identify stresses and challenges to this sector in Canada. The study also seeks to offer possible lessons for the direction of higher education policy in Australia and to raise concerns for the direction in Canada. The focus of the study is on the period since 2000 when consistent data for Canada largely became available. In 2005, the Rae Report – the last major overall review of higher education in Canada – was published followed by three volumes of evaluative studies of the state of higher education in Canada (Beach, Boadway and McInnis, 2005; Beach, 2005; and Iacobucci and Tuohy, 2005). So earlier and detailed commentaries are readily available from these sources. The present paper includes discussion of both universities as well as colleges that jointly make up the higher education sector in Canada. The perspective of the discussion is largely economic and heavily based on comparative statistics and the incentives they reveal. The paper proceeds as follows. The next section points out the major distinguishing features of the Canadian higher education system. Section 3 identifies a number of challenges and stresses the higher education sector has been facing in Canada. Then Section 4 examines some background influences on the higher education sector in both Australia and Canada. Section 5 then raises concerns about the growing role of metrics in higher education and the incentive issues they raise. And Section 6 concludes with some lessons to be considered in both countries’ tertiary education sectors.
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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.019 | 0.007 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".