Bibliographic record
Abstract
Anarchism is increasingly filling the role that Marxism did in the 1970s and 1980s, providing a new generation of academics and activists with a framework to make links between theory and practice and excavate the history of movements that have been ignored and marginalized. In fields such as philosophy, anthropology, history, and political science, many have been turning to anarchism to hold accountable the oppressive liberalism of the twenty-first century and a Marxism that is often burdened with a sclerotic scholasticism. As a result, anarchism as a theoretical project and as a subject of historical investigation has flourished over the last ten years. Three recent books demonstrate some of the diversity, sophistication, and energy of anarchist historical studies. In Beer and Revolution, Tom Goyens uses the insights of authors who cross political and epistemological craft lines, such as Michel de Certeau, Henri Lefebvre, and Edward Soja, to reveal how New York’s early German anarchist movement “produced space and inscribed it with meaning.” (7) Goyens uses the “spatial dimension” to focus on how the German anarchists established “a way of life in the here and now,” (8) and his meticulous research and spirited prose take us to the anarchist beer halls, clubs, schools, and picnics where the movement’s slogans and iconography were hung with care, the songs were sung with fervour, and the fiery speeches review essay / note critique
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.013 | 0.026 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".