Post-secondary Education in Crisis: The Decline of Social Mobility and the Future of Learning in Canada
Bibliographic record
Abstract
By 2040, Canada's post-secondary education (PSE) landscape is expected to have undergone a profound transformation, challenging its long-held status as a reliable pathway to upward social mobility. Historically, earning a college or university degree was viewed as a guaranteed route to stable employment, higher income, and improved social standing. However, predicted escalating tuition fees, soaring housing costs, extended program durations, and curricula misaligned with evolving job market demands will render PSE increasingly inaccessible to all but the wealthiest Canadians in a few short decades. This paper explores the socioeconomic consequences of these trends, including widening class divides, underemployment, skills mismatches, and the erosion of education's role as a public good. Drawing on government reports, labour market data, and emerging educational models, the analysis identifies sustainable alternatives such as modular micro-credentials, vocational and technical education, work-integrated learning, lifelong reskilling ecosystems, and community-based models. Ultimately, the study argues that for Canadian post-secondary institutions to remain relevant, they must embrace comprehensive reforms centred on affordability, flexibility, and more substantial alignment with contemporary workforce demands. Without such transformation, the risk deepens the polarization of opportunity, threatening both individual prospects and societal cohesion.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.021 | 0.007 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".