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Record W2942350015 · doi:10.3138/ijcs.57.x.3

Frontier Violence and Law and Order: Historical and Geographical Variance in the Great Plains of the North American West

2020· article· en· W2942350015 on OpenAlexvenueaboutno aff
Pierre M. Atlas

Bibliographic record

VenueInternational Journal of Canadian Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsFrontierLawlessnessLaw enforcementAmerican westHuman settlementGovernment (linguistics)LawPolitical scienceGeographyDevelopment economicsSociologyEthnologyArchaeologyEconomicsPolitics

Abstract

fetched live from OpenAlex

Stark differences between the United States and Canada in the post-Civil War/post-Confederation frontier West of the Great Plains and Prairies regarding the role of government, levels of interpersonal violence, and access to firearms (especially handguns) helped to shape the two countries’ divergent developmental paths. Utilizing the alternative approaches of Seymour Martin Lipset’s “origins thesis” and borderlands studies to structure its analysis, this article contrasts the frontier experiences of both countries in the nineteenth century concerning gun laws, violence, and the enforcement of law and order. Canada’s frontier West was demonstrably more orderly and peaceful than was the American frontier, yet the closer one came to the 49 th parallel, the more rowdy and violence-prone were the Canadian towns and settlements. Nevertheless, despite occasional instances of lawlessness, even the Alberta borderlands were not as violent or unruly as the American frontier, due in large measure to a strong central government and the effectiveness of the North-West Mounted Police.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.551
Threshold uncertainty score0.445

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 studies0.0000.001
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 head0.016
GPT teacher head0.242
Teacher spread0.226 · 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 designObservational
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

Citations1
Published2020
Admission routes2
Has abstractyes

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