Proving FTA Preferential Tariff Eligibility: The Evidentiary Burden in Canada
Bibliographic record
Abstract
As is the case with most free trade agreements, importers simply claim preferential tariff eligibility at the time of import. This claim can later be subject to verification by the customs administration in view of determining if it was valid. Proving preferential tariff entitlement requires assembling and presenting relevant facts and documents that support the claim. But just how much evidence is necessary in order to discharge that burden? In Canada there has always been a disconnect between what the Canada Border Services Agency (CBSA) deems necessary in the course of an origin verification and what the courts find satisfactory in the course of a judicial review. What follows are certain illustrations of that disconnect and how it usually gets resolved by Canadian courts. Origin verification, judicial review, NAFTA, burden of proof, non-originating status, eligibility considerations, evidence
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.077 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.018 | 0.013 |
| Scholarly communication | 0.020 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".