Bibliographic record
Abstract
In this book, Amy Lai examines the current free speech crisis in Western universities. She studies the origin, history, and importance of freedom of speech in the university setting, and addresses the relevance and pitfalls of political correctness and microaggressions on campuses, where laws on harassment, discrimination, and hate speech are already in place, along with other concepts that have gained currency in the free speech debate, including deplatforming, trigger warning, and safe space. Looking at numerous free speech disputes in the United Kingdom, the United States, and Canada, the book argues for the equal application of the free speech principle to all expressions to facilitate respectful debates. All in all, it affirms that the right to free expression is a natural right essential to the pursuit of truth, democratic governance, and self-development, and this right is nowhere more important than in the university.
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 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.025 | 0.013 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.079 | 0.058 |
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; both teacher heads agree on what is shown here.
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".