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Record W4378388748 · doi:10.1017/nps.2023.31

Nationalism and National Identity in North America

2023· article· en· W4378388748 on OpenAlexaffabout
Dillon P. Byrd

Bibliographic record

VenueNationalities Papers · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNationalismNational identityScholarshipPoliticsConstructiveGender studiesIdentity (music)Ethnic groupPolitical scienceSociologyLawAesthetics

Abstract

fetched live from OpenAlex

Abstract The study of nationalism in North America has focused heavily on national identity. Much of the scholarship in the region indicates that most individuals define their respective national identities as attainable and inclusive. In contrast to these findings, other evidence from nationalism and ethnic politics scholarship in North America suggests a strong racial link to national understandings. Focusing on national identity research in North America, primarily the United States, but also findings from Canada and Mexico, I try to address the connection between national identity, its political effects, and the boundaries of national identity content. This article identifies important findings from research in North America and proposes that scholars look beyond the current research to study national development – understood both historically and through the study of individuals’ constructive deployment of nationalism in everyday life.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.601

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0100.011
Scholarly communication0.0050.002
Open science0.0000.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.284
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2023
Admission routes2
Has abstractyes

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