Challenges and Drawbacks in the Marketisation of Higher Education Within Neoliberalism
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper addresses some of the challenges and drawbacks associated to the ongoing worldwide process of marketization (neoliberalization) in higher education. Neoliberalism—the prevailing model of capitalist thinking based on the Washington Consensus—has conveyed the idea that a new educational and university model must emerge in order to meet the demands of a global productive system that is radically different from that of just a few decades ago. The overall argument put forward is that the requirements, particularly the managerial and labor force needs of a new economy—already developing within the parameters of globalization and the impact of information and communication technologies (ICTs)—cannot be adequately satisfied under the approaches and methods used by a traditional university. Neoliberalism affects the telos of higher education by redefining the very meaning of higher education. It dislocates education by commodifying its intrinsic value and emphasizing directly transferable skills and competencies. Nonmonetary values are marginalized and, with them, the nonmonetary ethos that is essential in sustaining a healthy democratic society. In this paper I will address (1) some of the problems and shortcomings in the triple-helix model of university-industry-government collaborations, (2) the transformation of students into customers and faculty into entrepreneurial workers, highlighting the many drawbacks of such strategies, (3) the hegemony of rankings as procedures of surveillance and control, (4) the many criticisms posed against neoliberalization in higher education and the possible alternatives looking to the future.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it