Governance, leadership and economic growth in Singapore
Bibliographic record
Abstract
Although Singapore inherited the same British model of governance as other Commonwealth states, its governing system has become widely known for efficiency and competence, especially in terms of its role in generating an “economic miracle.” Economic growth has remained consistently high—at an average annual rate of 9.8 percent in the 1970s and 8.2 percent in the 1980s. Between 1988 and 1997, its Gross Domestic Product or GDP increased more than 2.5 times; between 1993 and 1997, it continued to rank very high in terms of its business-friendly environment; and by 1994, its per capita GDP (US$20,000) surpassed that of Australia, Canada, and the UK. These state-led economic achievements make Singapore a good case for studying contemporary reforms in governance based on the principle of the rolling back of the state’s economic management. While most countries have adopted the above mentioned business oriented governance reforms due to the alleged inefficiency and mismanagement of the public sector, the Singapore government has introduced such reforms despite its efficient and well-managed public sector. Moreover, although many developing countries with heavy external debt have adopted privatization and deregulation, liberalized trade and investment, and restructured their state bureaucracy according to the principles of the “New Public Management” (NPM), often in response to conditions imposed by international aid agencies, Singapore is virtually free from external debt and thus free from such direct external pressure to adopt these reforms.Against this context this article tries to explain the role of governance and leadership in administration which fostered economic growth in Singapore. Singapore governance system has been consistently rated by Transparency International as one of the most politically transparent and least corrupt governments in the world, but is also often being criticized for excessive interference in social issues.The article highlights how rapid socio economic transformation and quality of life was made possible through the ruling political party’s [PAP] brave attempt to liberalize the economy and attract foreign capital through various measures. The pervasive role of government is visible in all aspects of economic life in Singapore making it classic example of the direct relationship between transparency and economic 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".