From Plan to Market...Marketizing the Non-Economic: The economy of higher education: markets and marketization of Canadian post-secondary education
Bibliographic record
Abstract
This dissertation examines post-secondary education (PSE) through six case studies of criminal justice departments found in Canadian universities.It argues that postsecondary education is highly marketized in terms of demand but is more immune to market influences at the level of the state.The dissertation uses a relational analysis to examine relations between the state and post-secondary institutions.It identifies three primary markets in post-secondary education including academic labour and research markets, institutional finance markets, and student /labour and credential markets.Utilizing the concept of marketization, defined as a host of policy changes which seek to make institutions more accountable, the study assess the shift of post-secondary education toward a commercial and corporate form.I consider the institutions of post-secondary education as a constellation of power relationships between the state and institution, between institutions themselves, between professors and institutions, between professors and students, between institutions and students and between external forces such as markets and states, markets and institutions, markets and students, and markets and professors.The content of these relationships is determined by the intensity, character, and nature of their interdependences.This work seeks to reveal these relationships by examining the role of the state and various markets that constitute post-secondary education, what this looks like and its effect on the constitution of liberal arts education.This thesis argues that the current post-secondary academic form in Canada may be considered as a reflection of market practices and the operation of the state in a relational manner.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".