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Record W3208502978 · doi:10.3389/fsoc.2021.655880

Do Polarization Narratives Apply to Politics on the Periphery? The Case of Atlantic Canada

2021· article· en· W3208502978 on OpenAlexafffundabout
Rachel McLay, Howard Ramos

Bibliographic record

VenueFrontiers in Sociology · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsWestern UniversityDalhousie University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPoliticsNarrativePolitical scienceSociologyLawPhilosophy

Abstract

fetched live from OpenAlex

Researchers, policymakers, and the public often claim that "extreme" political views have become increasingly commonplace and that polarization on issues of race and immigration has become a central dilemma for contemporary politics. The popular narrative of political polarization captures tensions that many are noticing and experiencing. However, there is also significant confusion around the concept, as well as gaps between popular perceptions and empirical findings on the different forms of polarization and their prevalence across regions. It is unclear to what extent polarization describes a global phenomenon, as its national and subnational manifestations vary considerably, produced from distinct local histories as well as diffuse transnational forces. While the United States is often treated as ground zero for political polarization, nearby Canada does not appear to be experiencing polarization to nearly the same degree. Using data from a 2019 survey on Atlantic Canadians' political views and perceptions of change, this paper examines whether underlying forms of political polarization are manifesting in the region. We assess whether mass ideological polarization and partisan sorting can be found in Atlantic Canada, looking at socio-cultural and economic dimensions of political values. We also examine perceptions of polarization in the region, using Multiple Correspondence Analysis to observe underlying associations between perceptions, extreme or polarized views, and partisanship. This mapping approach provides insight into latent patterns often missed by more traditional methods.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.655
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.026
GPT teacher head0.314
Teacher spread0.288 · 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 designTheoretical or conceptual
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

Citations6
Published2021
Admission routes3
Has abstractyes

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