Bibliographic record
Abstract
If one forgets the past, he will not be prepared for the future. The Militia of Montana YES! TODAY JUST AS YESTERDAY. The Michigan Militia When the militia movement emerged in the United States during the mid 1990s its members were widely seen as simply the latest practitioners of what Richard Hofstadter famously called “the paranoid style in American politics.” There was much comfort to be had in this characterization. It fitted the militia movement into a long-standing model for understanding right-wing extremism in American life, one in which the principal characteristics of such extremism were readily understood: conspiratorial, Manichean, absolutist – if not apocalyptic – and, of course, paranoid. The problem with this approach, though, is that it tends to discourage any examination of mainstream culture's role in the creation or sustaining of those defined as extremists. It downplays the extent to which the pool of ideological resources employed by the extreme right exists not just on the margins of American life, but also in the very fabric of the American ideology. Little attempt is made to explore the extent to which the ideas and beliefs of these “extremists” are related to, and are drawn from, key periods in US history: from the American Revolution, the period of the constitutional settlement or the settling of the American West, for example. Yet such ideas and beliefs are absolutely central to how groups like the militias see themselves and the world around them.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.014 | 0.017 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".