MétaCan
Menu
Back to cohort
Record W3031545090

Fraud in land transaction: conflicting interest between registered proprietor and bona fide purchaser under the national land code 1965 / Noraffy Ahmad, Izzanee Ab Malek Foad and Haidatul Munira Hamzah

2012· article· en· W3031545090 on OpenAlexaboutno aff
Noraffy Ahmad, Izzanee Ab Malek Foad, Haidatul Munira Hamzah

Bibliographic record

VenueUiTM Institutional Repositories (Universiti Teknologi MARA) · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLand Rights and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsDatabase transactionOrder (exchange)BusinessLawCode (set theory)Law and economicsPolitical scienceEconomicsFinanceComputer science
DOInot available

Abstract

fetched live from OpenAlex

The numbers of fraud and forgery cases in land transaction are on the rise in Malaysia. Because of that, the issue of conflicting interest between the innocent parties such as the registered proprietor and the bona fide purchaser regarding their rights over the disputed land remains unresolved. It seems that the current Torrens System in Malaysia which applies the mirror and curtain principles as well as the provisions stipulated in the National Land Code 1965 is inadequate to protect the rights of both the registered proprietor as well as the bona fide purchaser with regards to cases of fraud and forgery in land transactions. Realizing this problem, this research paper will examine whether Malaysia can be considered as being at crossroads since it is currently facing a challenge as to whether it should adapt, implement and establish a Trust Assurance Fund as practiced in Canada and Australia in order to guarantee a complete protection for the innocent registered proprietor and bona fide purchaser involved in cases of fraud in land transactions.

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)0.008
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: none
Teacher disagreement score0.014
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.006
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.050
GPT teacher head0.248
Teacher spread0.199 · 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
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueUiTM Institutional Repositories (Universiti Teknologi MARA)Same topicLand Rights and ReformsFrench-language works237,207