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Record W2112495965 · doi:10.1177/1206331211412250

Road Signs on the Border

2011· article· en· W2112495965 on OpenAlexaff
Lee Rodney

Bibliographic record

VenueSpace and Culture · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsGeopoliticsMainstreamPoliticsGlobalizationTerrorismParallelsPolitical sciencePolitical economyBorder crossingSociologyLaw

Abstract

fetched live from OpenAlex

This article considers the political impact of a series of billboards that appeared at the Windsor–Detroit border and the Tijuana–San Ysidro border between 1991 and 2007. While there is a significant asymmetry between the political tensions on the northern and southern borders of the United States, there are remarkable parallels and relays between events that have taken place in major cities on these borders that indicate that generalized border anxiety has spread far beyond the localized territory of the southern borderlands. In this heightened climate of border insecurity, artists and community groups have seized on the geopolitical confusion that has emerged in mainstream American media where issues such as terrorism and illegal migration have often been folded into the same discourse. While border regions are tightly controlled spaces, these projects have served to highlight contradictory narratives of globalization and security, unmasking national insecurities that have been submerged through the bureaucratic discourses of the North American Free Trade Agreement and the more recent Smart Border agreements.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.004
Scholarly communication0.0050.004
Open science0.0000.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0210.002

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 head0.029
GPT teacher head0.294
Teacher spread0.265 · 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 designQualitative
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

Citations2
Published2011
Admission routes1
Has abstractyes

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