Exposing ideology within university policies: a critical discourse analysis of faculty hiring, promotion and remuneration practices
Bibliographic record
Abstract
Using critical discourse analysis (CDA), this paper exposes the neoliberal ideology of the knowledge-based economy embedded within university policies, specifically those that regulate faculty hiring, promotion, and remuneration in two national contexts: Turkey and Mexico. The paper follows four stages of CDA: (1) focus upon a social wrong in its language aspect; (2) identify obstacles to addressing the social wrong; (3) consider whether the social order in a sense ‘needs’ the social wrong; and (4) identify possible ways past the obstacles. The analysis demonstrates that the global, marketized climate of higher education has impacted Turkish and Mexican universities to such a degree that they have become increasingly corporate in their practices of management. The resulting effect is the creation of a performance culture that robs faculty of their professionalism. This paper uncovers this disadvantaged positioning of faculty and posits modest proposals for change.
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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 | 0.023 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.015 | 0.038 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".