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Record W3036774671

Firm Networks, Borders and Regional Economic Integration

2019· article· en· W3036774671 on OpenAlexaff
Mark Brown, Afshan Dar‐Brodeur, Jesse Tweedle

Bibliographic record

VenueAnalytical Studies Branch Research Paper Series · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCross-Border Cooperation and Integration
Canadian institutionsInnovation, Science and Economic Development CanadaStatistics Canada
Fundersnot available
KeywordsUpstream (networking)Downstream (manufacturing)Production (economics)BusinessUnit (ring theory)Industrial organizationSupply chainEconomic integrationValue (mathematics)International tradeEconomicsMicroeconomicsComputer scienceMarketingTelecommunications
DOInot available

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)0.005
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 score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0000.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.096
GPT teacher head0.467
Teacher spread0.371 · 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
Published2019
Admission routes1
Has abstractyes

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