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Record W4415696744 · doi:10.31261/rias.18635

The Canada/US Border: An International Boundary as Continental Cross-Section

2025· article· en· W4415696744 on OpenAlexaboutno aff
Nathaniel R. Racine

Bibliographic record

VenueReview of International American Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Health, Geopolitics, Historical Geography
Canadian institutionsnot available
Fundersnot available
KeywordsGeopoliticsPoliticsVernacularBoundary (topology)InterdependenceSpace (punctuation)Globalization

Abstract

fetched live from OpenAlex

This Editor’s Note opens the present issue of RIAS through a meditation on the Canada-US border not simply as a line of division but as a dynamic cross-section—one that can reveal the entangled geographies, cultures, and histories of North America. Drawing insight from across the disciplines of geography, literature, history, and environmental studies, it proposes the east-west border as a methodological lens through which to apprehend regional continuities and local specificities alike. Exploring a number of examples, the essay considers the border as simultaneously separating and connecting the two countries, paying special attention to vernacular landscapes that defy simplistic geopolitical readings. The essay further considers the symbolic and contested role of the Haskell Free Library and Opera House in Vermont, recently politicized by US authorities, as a lived space of permeability and intercommunity resilience. Ultimately, the border emerges here as a site where the global and the local, the political and the personal, intersect— offering a uniquely instructive vantage point on the interdependent realities of modern North America.

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)0.006
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.215
Threshold uncertainty score0.433

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.006
Science and technology studies0.0090.016
Scholarly communication0.0120.006
Open science0.0020.004
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.012
GPT teacher head0.406
Teacher spread0.394 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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