Bibliographic record
Abstract
I have a pessimistic view on the present and future of high education in general, and humanities in particular. As I see things, we face three main related problems. The first is what I would characterize as corporate control; the second, what I perceive as a class-divide enterprise; and the third as an attempt to limit the freedom of expression. I should add that my general impressions are mainly based on what I perceived within the North American higher educational system and in Europe, especially in England. Furthermore, I do not claim to be discovering something sociologically novel. What’s happening in higher education is a mere reflection of what’s going on in our neo-liberal capitalist society. My aim is modest. It mainly consists in highlighting how the neo-liberal and globalization (marketing) processes are affecting higher education and research. The conclusion doesn’t look rosy. Intellectuals, philosophers in particular, should take time to reflect on the current corruption of academia, and take a stance against the attack on the integrity of higher education.
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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.057 |
| Scholarly communication | 0.018 | 0.031 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".