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Record W6888891017 · doi:10.25316/ir-20402

Ideological Violence and Social Change in Canada and the United States from the 19th Century to Present Day

2025· dissertation· en· W6888891017 on OpenAlexaboutno aff

Bibliographic record

VenueVIUSpace (Vancouver Island University Library) · 2025
Typedissertation
Languageen
FieldSocial Sciences
TopicSociology and Norbert Elias
Canadian institutionsnot available
Fundersnot available
KeywordsIdeologySocial changeSocial orderOrder (exchange)Period (music)Social issuesCausality (physics)Poison control

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.648

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.224
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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