Information and Communications Technology Development Products Towards Strengthening Rural Communities in Malaysia
Bibliographic record
Abstract
This study aims to evaluate the extent of development of Information and Communication Technology (ICT) ability to empower rural communities and enhance their economic productivity. ICT is a core catalyst for the development of a country to achieve developed nation status. However, rural communities are still exposed to the challenges and constraints in order to promote ICT development in rural areas. To address this issue, the government has established various objectives to ensure that rural communities are not marginalized. In an effort to take advantage of ICT development in rural areas, governments and agencies have developed various ICT-based products in rural areas. Programs such as Center of Telecenter, Rural Internet Centre (PID), Medan Info Desa, e-Village/e-Community, K-TRAK, PKIT and others are among the products introduced to the rural community. The purpose of the introduction of this product is to focus on the government’s efforts in ensuring the development of balanced urban and rural areas from different angles. Through ICT products, a rural community not just only follows the development of the ICT revolution, but to create a knowledgeable society and helps to boost the quality of life of rural communities. Thus, this paper will discuss ICT products developed in the rural areas of Malaysia, the purpose and prospects of the product development and the challenges faced during its implementation. Hopefully, the discussion and recommendations given could trigger the opportunity and space in making ICT as a driving force to economic development in rural areas. Key words: ICT products; Rural communities; The use of ICT; Economic catalyst
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".