The Readiness of Malaysia Digital Economy: A Study of Three Government Policies from 1991 to 2020
Bibliographic record
Abstract
The Malaysian government has foreseen the importance of the digital economy to the nation since 1996. In 1996 and 1998, respectively, the Malaysia Digital Economy Development (MDEC) and Malaysian Communications and Multimedia Commission (MCMC) were established to regulate the industry and articulate digital economy initiatives both from public and private sectors. This study aims to review the digital economy policies introduced by three governments, i.e. Barisan Nasional, Pakatan Harapan and Perikatan Nasional, since the Independence in 1957 until 2020. Each ruling government has announced its digital economy initiatives as significant contributors to the national economic development. The review of the policies will include the Malaysia Plans, yearly budgets and economic stimulus packages. The outcome of this review will significantly help to evaluate the country’s readiness in embarking on the digital economy, and provide recommendations for future digital economy initiatives.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".