Bibliographic record
Abstract
Bringing together leading anthropologists, this collection sheds light on the vast topic of freedoms of speech from a comparatively human perspective.Freedoms of Speech provides a sustained, empirical exploration of the variety of ways freedom of speech is lived, valued, and contested in practice; envisioned as an ideal; and mediated by various linguistic, ethical, and material forms.From Ireland to India, from Palestine to West Papua, from contemporary Java to early twentieth-century Britain, and from colonial Vietnam to the contemporary United States, the book broadly interrogates the classic vision of a singular "Western liberal tradition" of freedom of speech, exploring its internal complexities and highlighting alternative perspectives on the relationship between speech, freedom, and constraint in various times and places.Chapters analyse subjects commonly linked to freedom-of-speech debates, shedding new light on familiar topics that include campus speech codes, defamation, and press freedom, while also exploring unexpected ones such as therapy, gift-giving, and martyrdom.These analyses not only provide unexpected perspectives and unique insights but also address a myriad of questions, contributing to a rich, interdisciplinary, and human understanding of the nature of freedom of speech.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.033 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".