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Record W2888706885 · doi:10.1111/twec.12706

Market access implications of non‐tariff measures: Estimates for four developed country markets

2018· article· en· W2888706885 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWorld Economy · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsConformity assessmentTariffMargin (machine learning)CertificationInternational economicsMarket accessTechnical barriers to tradeConformityEuropean unionEconomicsInternational tradeCustoms unionTrade facilitationBusinessDeveloping countryStraddleTrade barrierFinanceEconomic growthOperations management

Abstract

fetched live from OpenAlex

Abstract We quantify the effects of non‐tariff measures on the extensive margin of trade, examining the number of countries exporting particular products to Canada, the European Union, New Zealand and the United States. We find that non‐tariff measures that impose a conformity requirement, that is, testing, certification or inspection, will reduce the number of countries exporting to these markets. Conformity requirements imposed for sanitary or phytosanitary reasons have the largest effect in Canada, reducing the number of exporting countries by 47% compared to the situation where no compliance requirement is imposed. Conformity requirements imposed for other reasons covered by the WTO Agreement on Technical Barriers to Trade have the largest effect in Canada and New Zealand, reducing the number of exporting countries by 27% compared to the situation where no compliance requirement is imposed. However, we generally find a statistically significant positive effect for nontariff measures that do not impose a compliance burden, suggesting that such measures may facilitate 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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.091
GPT teacher head0.270
Teacher spread0.180 · 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