Third-party arrangements between private and public colleges in Ontario: benefits, threats, implications for policy
Bibliographic record
Abstract
Ontario’s Colleges of Applied Arts and Technology (CAATs) were established as an alternative public postsecondary choice for students to provide vocational education programmes to serve Ontario’s labour market. In the past 20 years years, neoliberal policies have pressured CAATs to be more entrepreneurial, efficient, and fiscally sustainable. Declining funding and enrolment and burgeoning demand from international students led some colleges to enter third-party arrangements (TPAs) with for-profit private career colleges (PCCs). This research used a qualitative research design to examine the development, growth and impact of TPAs between 2005 and 2019. Two overarching theoretical frameworks grounded the research: historical institutionalism (Streeck & Thelen, 2005) and Principal-Agent Theory (Mitnick, 1973; Ross, 1975). Document analysis and 25 semi-structured interviews were used to elucidate the trajectory of the formation, growth and cementing of TPAs into the Ontario college system. Inflection points were conceptualised to explain how decisions and conditions contributed to the trajectory. Competition, marketisation of higher education, economics, demographics and policies were seen as contributing to the formation, growth and formalisation of the TPAs. TPAs were perceived to introduce strategic risks to public colleges concerning future funding and enablement of PCCs, which have implications for system design, including further privatisation of Ontario’s public college system.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.016 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".