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Record W3112577312 · doi:10.18357/bigr21202019757

A The Tri-Border Area of Parana and COVID-19: A Tale Of Two Bridges in the South American Hinterland

2020· article· en· W3112577312 on OpenAlexvenueno aff
Juan Agulló

Bibliographic record

VenueBorders in Globalization Review · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Relations in Latin America
Canadian institutionsnot available
Fundersnot available
KeywordsBridge (graph theory)GeographyArchaeologyCoronavirus disease 2019 (COVID-19)Transversal (combinatorics)

Abstract

fetched live from OpenAlex

During the COVID-19 lockdown, at night on the stretch of the Parana River that goes from the Ponte Internacional da Amizade (International Friendship Bridge) south to the geographic trifinium, where the river splits and three borders meet, the sound of outboard motors and gunfire has intensified. Seven-and-a-half miles (twelve kilometres) of border space separate Brazil from Paraguay in South America’s hinterland. Since 1965, the main transversal gates of a long-shared border of 848 miles (1,364 kilometres) are located on both sides of the Amizade Bridge. In 2020, during the pandemic, work on a second bridge, started the previous year, was intensified. This essay focuses on the study of the border space between both infrastructures: the old and the new.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.004
Scholarly communication0.0020.003
Open science0.0000.002
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 head0.031
GPT teacher head0.412
Teacher spread0.381 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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