MétaCan
Menu
Back to cohort
Record W2185202334 · doi:10.19030/iber.v12i9.8047

Mexico's Drug War Is Hindering The Growth Of The Retail Sector Of Texas Border Cities

2013· article· en· W2185202334 on OpenAlexaboutno aff
Rutilio Martinez

Bibliographic record

VenueInternational Business & Economics Research Journal (IBER) · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Illicit Activities, and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Drug traffickingRetail salesSpanish Civil WarBusinessDevelopment economicsPolitical scienceEconomyGeographyEconomic growthEconomicsCriminologyLawSociologyMarketingArchaeology

Abstract

fetched live from OpenAlex

Between the first quarter of 2007 and the first quarter of 2012, the retail sales of Texas' border cities grew at an unprecedented low quarterly rate of 0.21%. Mexico's drug war contributed significantly to this low growth by hindering the growth of sales to Mexicans who cross the border to shop. This hindrance is likely to continue as long as Mexico's war on drugs continues to generate high levels of violent crime in the northern part of the country.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0040.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.056
GPT teacher head0.336
Teacher spread0.280 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueInternational Business & Economics Research Journal (IBER)Same topicCrime, Illicit Activities, and GovernanceFrench-language works237,207