How Universities Have Betrayed Reason and Humanity—And What's to Be Done About It
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
In 1984 the author published From Knowledge to Wisdom, a book that argues that a revolution in academia is urgently needed, so that problems of living, including global problems, are put at the heart of the enterprise, and the basic aim becomes to seek and promote wisdom, and not just acquire knowledge. Every discipline and aspect of academia needs to change, and the whole way in which academia is related to the rest of the social world. Universities devoted to the pursuit of knowledge and technological know-how betray reason and, as a result, betray humanity. As a result of becoming more intellectually rigorous, academic inquiry becomes of far greater benefit to humanity. If the revolution argued for all those years ago had been taken up and put into academic practice, we might now live in a much more hopeful world than the one that confronts us. Humanity might have begun to learn how to solve global problems; the Amazon rain forests might not face destruction; we might not be faced with mass extinction of species; Brexit might not have been voted for in the UK in 2016, and Trump might not have been elected President in the USA. An account is given of work published by the author during the years 1972–2021 that expounds and develops the argument. The conclusion is that we urgently need to create a high-profile campaign devoted to transforming universities in the way required so that humanity may learn how to make social progress toward a better, wiser, more civilized, enlightened world.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| 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