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Record W1493341244

Damages Under the UN Sale of Goods Convention

2013· article· en· W1493341244 on OpenAlexaboutno aff
Peter J. Mazzacano

Bibliographic record

VenueSSRN Electronic Journal · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicLaw, logistics, and international trade
Canadian institutionsnot available
Fundersnot available
KeywordsDamagesSupreme courtLawConventionCompensation (psychology)Position (finance)Law and economicsBusinessPolitical scienceEconomics
DOInot available

Abstract

fetched live from OpenAlex

This article provides an overview of damages under the United Nation Convention on Contracts for the International Sale of Goods (“CISG”) and compares how they differ from what might be typical under Canadian provincial sale of goods law. CISG Article 74 establishes the basic principles concerning recovery and the calculation of damages, and it reflects the general principle of full compensation (not unlike the Supreme Court’s “actual loss”). In contrast with the common law system, which requires that a loss be contemplated by both parties, the CISG makes it clear that it is foreseeability of the breaching party that is of legal significance. In addition, the CISG’s foreseeability test is both subjective and objective: the party may be held liable not only for losses which it actually foresaw, but also for losses which it “ought to have foreseen.” Thus, to make a party liable, it is not necessary to prove that the party actually foresaw the loss in question, as long as it was in a position to reasonably foresee the loss.

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)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.362
Threshold uncertainty score0.721

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0050.004
Scholarly communication0.0070.003
Open science0.0020.003
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.015
GPT teacher head0.227
Teacher spread0.212 · 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 designTheoretical or conceptual
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
Published2013
Admission routes1
Has abstractyes

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