Information Control, Loss of Autonomy, and the Emergence of Political Extremism
Bibliographic record
Abstract
INTRODUCTION Political extremism is a multidimensional phenomenon. It can be taken to refer to, for example, the tail ends of the distribution of worldviews and beliefs held by individuals in a society, the kind of objectives sought, the means used in the pursuit of those objectives, or the preeminent position accorded to one specific issue over all others. In this chapter, we focus on a particular dimension of extremism – namely the intolerance, unwillingness to compromise, and rejection of evidence contradicting one's beliefs that are often associated with the phenomenon. We look at the forces, within a social environment, that can contribute to the development of the above attitudes (Section 2). We then look at mechanisms that help reinforce and diffuse extreme positions (Sections 3 and 4). Much of what we say in these sections applies to all forms of extremism – whether religious, social, scientific, cultural or political. We focus on the last. Political extremism becomes a socially relevant phenomenon when it involves the mobilization of individuals and the formation of groups that pursue objectives and make use of means that impose external costs deemed to be unacceptable.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".