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Record W2514335108 · doi:10.5539/jpl.v9n7p279

Citing Responsibility for Enforcement Despite Contractual Liability in Compensation Expense, Injured in Jurisprudence and Iranian Law

2016· article· en· W2514335108 on OpenAlexvenueno aff
Alireza Hasani

Bibliographic record

VenueJournal of Politics and Law · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicInsurance and Financial Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsHarmLiabilityObligationBreach of contractBusinessLegal liabilityDamagesEnforcementJurisprudenceExclusion clauseLawStrict liabilityCompensation (psychology)DelictPrivity of contractLaw and economicsSeverabilityContract managementEconomicsPolitical sciencePrivate lawFinancePublic lawBlack letter law

Abstract

fetched live from OpenAlex

Civil liability, contractual liability, and unconventional have two branches. If there is a contract between two or more persons and one of them committed a breach of contract (failure to perform, delay in performing the obligation) to and to harm the other party is incomplete and should the contract have contractual liability for damages cope. Where does harm to another person without a contract exists between them or if there is a contract, Inflict losses not related to the contract, the talk of non-contractual liability. About whether contractual and non-contractual obligations is two different legal system or single legal system form, there is disagreement among the lawyers: Some distinguish these two systems from each other. But others believe that because the purpose of civil liability is to compensate for losses, these two are the single legal system. By examining the different opinions, we see that both contractual and non-contractual liability system distinct from each other. And despite the contract, the victim can rely on the rules of non-contractual liability.

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)0.007
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.020
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0100.031
Scholarly communication0.0080.006
Open science0.0020.004
Research integrity0.0100.007
Insufficient payload (model declined to judge)0.0040.000

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 head0.027
GPT teacher head0.263
Teacher spread0.237 · 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 designNot applicable
Domainnot available
GenreOther

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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