MétaCan
Menu
Back to cohort
Record W2952764888 · doi:10.1111/jors.12456

Firm networks, borders, and regional economic integration

2019· article· en· W2952764888 on OpenAlexaff
W. Mark Brown, Afshan Dar‐Brodeur, Jesse Tweedle

Bibliographic record

VenueJournal of Regional Science · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Economics and Spatial Analysis
Canadian institutionsInnovation, Science and Economic Development CanadaStatistics Canada
Fundersnot available
KeywordsMicrodata (statistics)Economic integrationIdentification (biology)EconomicsInternational tradeInvestment (military)Trade barrierBusinessInternational economicsEconomic geography

Abstract

fetched live from OpenAlex

Abstract Borders reduce interprovincial trade relative to intraprovincial trade. Using trade and firm ownership microdata over a 9‐year period (2004–2012), we show firm ownership networks, like trade flows, diminish with distance and borders and that the estimated effect of provincial borders on trade may fall by almost 75% after accounting for firm networks. This suggests the weaker presence of firm networks across borders has a significant, although statistically imprecise, effect on interprovincial trade. These findings reinforce the view that understanding border effects require not only the identification of barriers to trade but also barriers to investment across borders.

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)0.008
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 score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.022
GPT teacher head0.231
Teacher spread0.209 · 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

Citations17
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Regional ScienceSame topicRegional Economics and Spatial AnalysisFrench-language works237,207