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Record W2559742704 · doi:10.5539/jpl.v9n10p126

A Comparative Study of Damages and Price Reduction Remedy for Breach of Sale Contract under CISG, English and Iranian Laws

2016· article· en· W2559742704 on OpenAlexvenueno aff
Ali Zareshahi

Bibliographic record

VenueJournal of Politics and Law · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean and International Contract Law
Canadian institutionsnot available
Fundersnot available
KeywordsDamagesBreach of contractLawBusinessLegislatorPaymentCompensation (psychology)Order (exchange)Unjust enrichmentChoice of lawLaw and economicsEconomicsLegislationConflict of lawsPolitical scienceFinance

Abstract

fetched live from OpenAlex

<p class="cc">In order to discourage people from breaching a contract and also to compensate the injured party for any losses, the law provides several remedies for breach of contract. One of these remedies is price reduction. In this study, we aims to compare the rules of Iranian law for price reduction remedy with those provided by Convention on Contracts for the International Sale Of Goods (CISG), and English law. English law has set detailed rules for rewarding damages for breach of contract , while Iranian law has generally-defined rules. The legislator has not determined not only the types of damage, but also the criteria for assessment of the damage. The remedies provided for price reduction in the CISG for breach of contract has been adapted to requirements of international trade, while In Iranian law there is no clear rules for this purpose, except three rules including a) Giving property to the buyer instead of money, (b) Compensation for loss of legitimate business involved to the buyer, and (c) Compensation for delayed payment to the buyer.</p>

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.916
Threshold uncertainty score0.133

Codex and Gemma teacher scores by category

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

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 head0.044
GPT teacher head0.344
Teacher spread0.300 · 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 teacher head, 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
Published2016
Admission routes1
Has abstractyes

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