The Role of Efficient Urban Governance in Managing Kuala Lumpur City-Region Development
Bibliographic record
Abstract
This paper discuss on the preliminary study on the concept of efficient in urban governance towards managing development of Kuala Lumpur City-Region. City-region development has been a major issue in the country’s latest development agenda. The issue is more obvious in city-region due to its role as an engine of growth economy development. Now, with its sights set on attaining the economic level of a fully developed nation by 2020, Malaysia must focus on securing a credible share of the lead sectors of the globalised economy. Kuala Lumpur City-Region, which is the most developed region in the country and an important catalyst towards national economic growth. How well do urban governance responsible to efficiency and effectiveness of local authorities in city-region? What kind of urban governance is required to enhance competitiveness and earning opportunities within city-region? The main challenge of enhancing city competitiveness in city-region is efficient urban governance. The world today needs a new, comprehensive and holistic model of urban governance that involves all sectors (government, business and the civil society) as equal partners in development. Urban governance which integrates all sectors including public, private and other social organisations in participatory decision making. Efficient urban governance is characterized by sustainability, subsidiarity, equity, efficiency, transparency and accountability, civic engagement and citizenship and security. In line with this, the importance efficient urban governance would make Malaysia more competitive and attractive to investors and facilitate the achievement of the nation’s development goals. Therefore Kuala Lumpur City-Region will manage and govern efficiently.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".