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Record W7048608542

A legal study on Malaysian contract law: economic duress and doctrine of unconscionability / Nur Liyana Mohd Norizam, Nurul Izzah Mohd Nazri and Puteri Farahwati Faizan

2012· other· en· W7048608542 on OpenAlexaboutno aff

Bibliographic record

VenueUiTM Institutional Repositories (Universiti Teknologi MARA) · 2012
Typeother
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSubpoenaNucleofectionPretextCircumstantial evidenceHyporeflexiaTSG101
DOInot available

Abstract

fetched live from OpenAlex

The Contracts Act 1950 (Malaysia) is an old statute which basically adopted after the Indian Contract 1872. When there is lacuna in the law, our court will refer to English Common Law before the cut off dates to fill up the lacuna as provided under section 3 and 5 of Civil Law Act 1956. Nonetheless, these archaic laws are incapable to govern issue in present time. Furthermore, the development of laws around the world especially in this era of globalization ICT development causes our laws to grow as well. Some of the disputes which are now rising out of the agreement or contract between parties are that the existing contract laws in Malaysia are unable to solve some problems, such as issues on economic duress and unconscionability. Thus, this causes problem to our legal system.In order to curb this problem, our research will be focusing on the issue on economic duress and the doctrine of unconscionability in which our Contract Act 1950 is silent. These provisions are already developed in other countries, such as United States and Canada. This research will analyse the above issues with reference to the Malaysian Contract law, United Kingdom Law, United States Law and Canadian Law.

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)0.004
metaresearch head score (Gemma)0.008
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: Empirical · Consensus signal: none
Teacher disagreement score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0050.015
Scholarly communication0.0070.007
Open science0.0010.002
Research integrity0.0030.004
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 head0.011
GPT teacher head0.229
Teacher spread0.218 · 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
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
Published2012
Admission routes1
Has abstractyes

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