Reanimating Anarchist Geographies: A New Burst of Colour
Bibliographic record
Abstract
Abstract: The late nineteenth century saw a burgeoning of geographical writings from influential anarchist thinkers like Peter Kropotkin and Élisée Reclus. Yet despite the vigorous intellectual debate sparked by the works of these two individuals, following their deaths anarchist ideas within geography faded. It was not until the 1970s that anarchism was once again given serious consideration by academic geographers who, in laying the groundwork for what is today known as “radical geography”, attempted to reintroduce anarchism as a legitimate political philosophy. Unfortunately, quiet followed once more, and although numerous contemporary radical geographers employ a sense of theory and practice that shares many affinities with anarchism, direct engagement with anarchist ideas among academic geographers have been limited. As contemporary global challenges push anarchist theory and practice back into widespread currency, geographers need to rise to this occasion and begin (re)mapping the possibilities of what anarchist perspectives might yet contribute to the discipline.
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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 | 0.019 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.009 | 0.035 |
| Scholarly communication | 0.018 | 0.022 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.013 | 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".