Experiencing Relative Deprivation as True Crime: Applying Cultural Criminology to the Qanon Superconspiracy Theory
Bibliographic record
Abstract
This essay builds upon earlier studies of the QAnon superconspiracy theory by applying cultural criminology as a framework to investigate the significance of QAnon and the events that facilitated the rise of the superconspiracy and the associated political movement. QAnon has had multiple impacts that should be of interest to criminologists. In the United States, QAnon was involved with the 2020 election, as adherents believed messages posted by "Q" referred to President Trump as a messiah and Trump tacitly acknowledged the group. In addition, QAnon has international influence, most recently in the "trucker" convoy in Canada and anti-vaccine protests in New Zealand and Germany. This essay utilizes cultural criminology to introduce the framework of relative deprivation theory and emphasize the importance of the gaze from above and below in structuring relative deprivation. In addition, we discuss the role of cultural understandings of victimization in shaping ideology and physical frameworks used by QAnon.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.008 | 0.058 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".