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Record W7010112048

GST implementation in Malaysia: government adoption and initiatives / Heldah Rolland

2015· other· en· W7010112048 on OpenAlexaboutno aff

Bibliographic record

VenueUiTM Institutional Repositories (Universiti Teknologi MARA) · 2015
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicTaxation and Compliance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Work (physics)Taxable incomeCircumstantial evidencePopulationRevenue
DOInot available

Abstract

fetched live from OpenAlex

Goods and Services Tax (GST) or also known as Value Added Tax ( VAT ) has been implemented in 160 countries. In Malaysia, the implementation of GST is to replace the Sales and Services Tax which has been used by the country for years. The similarity of GST and Sales and Services Tax is they are a form of indirect tax since the Government cannot directly collect the taxable amount from individuals. The tax amount is recovered by the Government through sellers which is collectable during sales transaction. With the implementation of GST. the Government hopes to collect more proceeds to increase its national revenue and reduce the country's debt. However, since the implementation of GST, the Government has been receiving numerous responses from the public who are still in doubt whether its implementation will be able to achieve the objectives as set out by the Government. The purpose of this study is to identify whether the Government has carried out a thorough analysis and survey before implementing GST. Also, whether GST is based on adoption basis and whether Government agencies such as Kementerian Perdagangan Dalam Negeri Koperasi Dan Kepenggunaan (KPDNKK), Royal Malaysian Customs Department (RMCD) and Department of Information are ready to accept with support the GST system in Malaysia. The findings of the research show that the Government has not done any detailed study regarding the implementation of GST. This study used information on G S T implementation and planning strategies of various countries such as Singapore, New Zealand, Canada and India as comparison. This study found that these countries have conducted a thorough study and research before implementing GST in their countries. In addition, these countries have taken several initiatives to receive tremendous support from their citizens. The recommendation of this study is that more research should be carried out so that further improvement could be made to the existing GST system in the country.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.046
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.025
GPT teacher head0.236
Teacher spread0.212 · 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
Published2015
Admission routes1
Has abstractyes

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