Stand against the wiles of the devil. Interpreting QAnon as a Christian extremist movement
Bibliographic record
Abstract
QAnon has become a prominent domestic security threat in recent years due to the involvement of its supporters in violent terrorist and criminal acts. Numerous QAnon supporters participated in the 2021 U.S. Capitol Storming and the 2022 Freedom Convoys in Canada, committing criminal violent and non-violent acts. When analysing these events, researchers have observed that numerous QAnon supporters have been influenced by religious and spiritual beliefs, emphasising the importance of QAnon's religious dimensions and their impact on individuals' radicalisation. However, academics have not explored such religious dimensions by drawing upon the body of literature from the field of religious studies, thus overlooking core facets of QAnon's religious dimensions. By conducting an empirically driven research based on the collection and analysis of QAnon religious imagery downloaded from QAnon- related Telegram channels, this dissertation aims to analyse QAnon's religious dimensions and hypothesise about the potential impact of religious extremism on its affiliates' propensity to violence. The visual analysis conducted by applying both semiotics and hermeneutics to QAnon religious imagery shows that QAnon can be labelled as a Christian extremist movement that shares commonalties with the religious phenomena...
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".