Bibliographic record
Abstract
The parallels between the January 6th, 2021, attack on the U.S. Capitol and the so-called “March on Rome” of October 1922, are unmistakable, from Donald Trump and Benito Mussolini’s leadership styles to their non-participation in the actual coup attempts to the unwavering commitment of their most zealous followers to the respective causes. Indeed, comparisons between these two figures and events have led scholars to refer to the events on January 6th as a “Half-Baked March on Rome” or an “abortive March on Rome,” among other similar references. While historically convenient and rhetorically appealing, however, these associations risk downplaying the requisite conditions that allowed the March on Rome to result in a successful coup but which never manifested in the buildup to January 6th or its actualization. Moreover, referring to January 6th within the context of the March on Rome minimizes the distinct possibility that the former was but the precursor to an eventual triumphant American iteration of the March on Rome. By using the March on Rome as a conduit through which to examine the January 6th, 2021, attack on the U.S. Capitol, this paper seeks to properly place the latter within the context of significant revolutionary events of the past and thereby explore its role in the broader arc of American democracy's future.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".