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Record W3112761279 · doi:10.18357/bigr21202019835

The Central U.S.–Mexico Borderlands during the 2020 Pandemic

2020· article· en· W3112761279 on OpenAlexvenueno aff
Kathy Staudt

Bibliographic record

VenueBorders in Globalization Review · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Health, Geopolitics, Historical Geography
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicRhetoricCoronavirus disease 2019 (COVID-19)RefugeePolitical science2019-20 coronavirus outbreakNationalismSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Economic growthDevelopment economicsPublic administrationGeographyLawVirologyPoliticsMedicine

Abstract

fetched live from OpenAlex

This essay begins by setting the scene of the 2020 novel coronavirus virus (COVID- 19) pandemic in the central U.S.–Mexico borderlands. The essay then outlines the pre-pandemic situation, from 2016-2019, one characterized by larger numbers of migrant arrivals from Central America, harsh U.S. anti-refugee and anti-Mexican practices, and hardened border controls. The article then discusses pandemic-linked deaths and closures of the border to all but U.S. citizens and Legal Permanent Residents and to slightly diminished cargo traffic, rising again by July and numbers of COVID-19 deaths declining thereafter. Official U.S. border rhetoric has broadened to strengthen nationalist security rationales around health, while activists push back against harsh policy practices, creating an ongoing, dynamic tension in the borderlands.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0030.003
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.315
Teacher spread0.300 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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