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Record W1893596784

Internet Activities among Malaysian Insurance Companies

2005· article· en· W1893596784 on OpenAlexvenueno aff
Ainin Sulaiman, Noor Ismawati Jaafar, Tee Chee Kiat

Bibliographic record

VenueThe Journal of Internet Banking and Commerce · 2005
Typearticle
Languageen
FieldComputer Science
TopicCybercrime and Law Enforcement Studies
Canadian institutionsnot available
Fundersnot available
KeywordsThe InternetBusinessFinancial servicesInvestment (military)MarketingFinancePlan (archaeology)Internet privacyWorld Wide WebComputer science
DOInot available

Abstract

fetched live from OpenAlex

Many studies have been conducted to study Internet usage. Most of them focused on SMI/SME, individuals, services organisations including the financial sector. Previous studies on Internet usage in the financial sector in Malaysia were more focused towards the banking institutions. Not much information is available with regards to the Internet usage among insurance companies. Recognizing the potential of the Internet to insurance companies, the Central Bank of Malaysia (Bank Negara of Malaysia) has established guidelines that allow insurers to offer their services online. This study describes the extent of Internet usage among Malaysian insurers. Some insurers have already begun to use the Internet to conduct their daily business transactions, some are in the midst of planning to use and some do not have plan to use at all. Many of them stated that security, customer readiness and cost of initial investment were important considerations when deciding to adopt Internet technologies.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.241
Teacher spread0.221 · 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 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

Citations3
Published2005
Admission routes1
Has abstractyes

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