Multi-Criteria Decision-Making Analysis of Information and Communication Technology Using VIKOR
Bibliographic record
Abstract
The utilization of Information and Communication Technology (ICT) has greatly enhanced various sectors in modern societies. With the rapid advancement and widespread adoption of ICT across different fields, it now plays a significant role in both economic and social development. Recognizing the positive and negative effects of ICT, governments continually strive to propose improved policies and recommendations for enhancing their ICT infrastructure. However, the formulation of effective policies relies on a thorough understanding of past and present policies in order to develop better proposals. To assess ICT development and its impact on society, an integrated social and economic indicators MCDM (Multi-Criteria Decision Making) approach is employed. This approach involves comparing six key indicators: ICT employment, ICT goods exports, ICT investment, ICT value addition, and Internet access. By evaluating the performance of these indicators, a comparison can be made among the G7 countries. Notably, countries like Italy and Canada demonstrate relatively weaker performance in terms of ICT development.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".