Bibliographic record
Abstract
This chapter maintains that in order to understand anti-fascism as a global historical phenomenon, historians should start with reactions to fascism in the 1920s, rather than the 1930s. Italy was the birthplace of the fascist and anti-fascist struggle, but as Copsey shows, this struggle soon had global reach, extending to Italian diasporic communities across several continents. Focusing on four cases from the English-speaking world (US, Canada, Britain, Australia), this chapter reveals how anarchists formed the vanguard of the earliest anti-fascist opposition. Copsey underscores the importance of radical fulcra, key figures emerging as anti-fascist figureheads. In some instances, there was recourse to ‘diasporic nationalism’ (an alternative to proletarian internationalism), and in some cases, to violence. Yet there was also significant variation in this diasporic experience: there was greater nuance to it than is commonly thought.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".