Bibliographic record
Abstract
Increasingly, scholars are examining the ways in which the Internet allows the hate movement to retrench and reinvent itself as a viable collective. The many electronic means available to the movement – blogs, newsgroups, ’zines, etc. – allow an ease of communication and dissemination of their views never before possible. While there are obvious points of convergence across the various Klan groups, or identity churches, or skinhead organizations, the hate movement has historically been varied and, in fact, fractured. Internet communication facilitates the creation of the collective identity that is so important to movement cohesiveness. Clearly, this has strengthened the domestic presence of these groups in countries like the United States, Germany and Sweden. Yet relatively less attention has been paid to the way in which the Web facilitates the consolidation of a global movement. Internet communication knows no national boundaries. Consequently, it allows the hate movement to extend its collective identity internationally, thereby facilitating a potential ‘global racist subculture’. It is this process that we seek to uncover in this paper, with an eye to thinking about ways to intervene so as to weaken the impact.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.044 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".