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Record W4323037975 · doi:10.4018/ijsr.319023

Paving the Road to Global Markets

2023· article· en· W4323037975 on OpenAlexaffabout
Diane Liao, Michelle Parkouda

Bibliographic record

VenueInternational Journal of Standardization Research · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsCanadian Standards Association
Fundersnot available
KeywordsConformity assessmentTechnical barriers to tradeObstacleTariffBusinessTechnical standardTrade barrierInternational marketInternational tradeConformityMarket accessInternational economicsEconomicsPolitical scienceOperations managementGeography

Abstract

fetched live from OpenAlex

While tariff barriers have drastically reduced around the world, non-tariff barriers, including demonstrating compliance with technical regulations, standards, and conformity assessment procedures, remain a significant obstacle to trade and could be particularly daunting for small and medium enterprises (SMEs). International standards have been recognized as an effective way to reduce technical barriers to trade (TBT). This research examines the impact of Canada's participation in international standards development (measured by technical committee/subcommittee participation) on SMEs' likelihood to export. Drawing on a national SME survey, results of the analysis showed that, after controlling for potentially confounding firm and owner attributes, Canada's participation in international standards development has a positive impact on Canada's exports and is associated with engaging more SMEs in international trade.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.064
Threshold uncertainty score0.193

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.004
Scholarly communication0.0100.013
Open science0.0010.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0580.006

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 head0.168
GPT teacher head0.382
Teacher spread0.213 · 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 designNot applicable
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

Citations3
Published2023
Admission routes2
Has abstractyes

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