Ideological Violence and Social Change in Canada and the United States from the 19th Century to Present Day
Bibliographic record
Abstract
In recent years, Canada and the United States have revised national security and public safety priorities to address the domestic threat of extreme social violence that emerges from social, political, and religious views and beliefs that challenge the social order. An imminent threat, extreme ideological views, and movements can inspire like-minded individuals by promoting an idealized social order through enduring stereotypes that elevate their status, sometimes through violence. Developed using a pragmatic approach, this study addresses these views and movements when they devolve into violent acts. A socio-historical exploration, this study explores social change and Canadian and American historical elements from the 19th century to the present day, linking them with ideological and ideologically themed violence. In order to address the research question, does social change influence rates of ideological violence?, Norbert Elias’s civilizing theory and Cas Wouters’s seven social balances (Wouters, 2014) are employed to illustrate the social change of the time period. Further, it introduces the analytical concept of ideological themes, where causality cannot be immediately confirmed, to resolve recently formed definitions, such as mixed and composite ideologies. Laying the groundwork for future study areas, the findings propose an applied approach to developing social policies that foster social change that may curtail the destructive aspects of individual and group ideologies.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.038 | 0.023 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".