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Record W2592571507 · doi:10.5539/jpl.v10n2p188

Legal-Juridical Analysis of the Basis and Impact of Harmful Contracts on the Relations of the Sides and the Third Parties under the Act 2014 of the Way of Implementing Financial Sentences

2017· article· en· W2592571507 on OpenAlexvenueno aff
Mahboobeh Mina, Mehdi Sokhanvar, Davood Jahanbazi, Seyyed Hoseyn Hoseyni Rechi

Bibliographic record

VenueJournal of Politics and Law · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicInsurance and Financial Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsHarmRelation (database)Subject (documents)JurisprudenceLaw and economicsLawPolitical scienceBusinessSociologyEconomicsComputer science

Abstract

fetched live from OpenAlex

Given the relativity principle of contracts their impacts in proportion to third parties are an exceptional issue. In a possible assumption there is a possibility of harm and damage to a third party because of the contract between two people. In our juridical texts, some religious experts have sporadically in a topic of jurisprudence stated the instances of these contracts and have considered two theories of validity and invalidity about them. On the basis of this assumption, although the law of the way of implementing financial sentences considered hanged in 2014 but its 21st article with a bit of expansion has considered the former result. Therefore concerning these contracts by considering the valuable rule of the principle of no harm, we can accept the theory of relative lack of influence. Given the importance and role of the contracts in the life of community members and the lack of determining the influence of such contracts in legal and juridical texts the analysis of these impacts seems to be necessary. In the present article by analyzing the subject in legal and juridical texts of Iran the influence of these contracts in the relation between the parties and in proportion to third party is analyzed.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.748
Threshold uncertainty score0.568

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.026
GPT teacher head0.264
Teacher spread0.238 · 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 designObservational
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
Published2017
Admission routes1
Has abstractyes

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