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Record W3159115592 · doi:10.19166/glr.v1i1.2800

Harmonization of Laws on Electronic Contracts Based on International Instruments for the ASEAN Economic Community

2021· article· en· W3159115592 on OpenAlexaff
Andrew Betlehn

Bibliographic record

VenueGlobal Legal Review · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinTech, Crowdfunding, Digital Finance
Canadian institutionsCentre for Global Health Research
Fundersnot available
KeywordsHarmonizationEconomic communityBusinessMember statesInternational tradeElectronic signatureAccountingEconomicsEconomyEuropean union

Abstract

fetched live from OpenAlex

Technological advancement has created new business practices such as utilizing electronic contracts. Utilization of electronic contracts, especially in international transactions, has pushed countries around the world to impose new regulations defining the legalities of electronic instruments. Challenges arise considering the global and borderless nature of electronic transactions faced with regulations of different countries that are not in sync with each other. This is especially apparent in Member States of the ASEAN Economic Community. This paper attempts to discover the ideal legal framework for electronic contracts in the ASEAN Economic Community. Based on the research and analysis, it has been found that there is a need for a harmonized legal framework regarding electronic commerce that can be adopted unaltered by Member States of the ASEAN Economic Community, which could be drafted by the ASEAN as an inter-governmental organization.

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)0.029
metaresearch head score (Gemma)0.036
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 score0.050
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.004
Science and technology studies0.0040.005
Scholarly communication0.0090.005
Open science0.0020.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.022
GPT teacher head0.274
Teacher spread0.252 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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