Bibliographic record
Abstract
The first and the second editions of the South Asian Economic Development (SAED) were published, respectively, in 1999 and 2010. Both the editions enjoyed highly satisfactory demand from users all over the world, most importantly in the UK, US, and EU nations. Both the editions have attracted reviews from top international journals on development and regional studies. The concluding quarter of the 20th century has been a ‘golden era’ for South Asia, both politically and economically. Politically, on the one hand, the region remained calm except for a civil war, which continued for more than 30 years in Sri Lanka. India and Pakistan have remained relatively calm with only a few border skirmishes. In Bangladesh, surprisingly, two warring political parties took turns winning general elections in 1991 and 1996 after almost two decades of autocratic military rule from 1975 to 1990. Calm in the political arena in India and Pakistan has contributed to steady growth in these economies since 1990, which resulted in good progress towards achieving high levels of development activities. Also, in Bangladesh and Pakistan, after years of military rules, state power was transferred to civil politicians through legitimate democratic processes. The chapters of the first edition in 1999 carried out materials about economic transformation, opportunities, and challenges of the four South Asian nations over the immediate past two decades. The second edition was published in 2009, covering the early period of MDGs and the development impacts on South Asia. The first edition had enjoyed high demand from users, as suggested earlier, which made Routledge invite the authors to work for the second edition within a limited time frame. It appears now that the second edition had enjoyed good user demand too, over a longer period, 2009–2020. This has made Routledge, once again, invite the authors to begin work on the third edition by January 2023. In one count it shows, more than 500 libraries worldwide are now the home of both hard and soft copies of the second edition. The third edition, of course, as readers and followers of SAED over the last two decades would know, is going to be challenging as far as the development of these four countries of South Asia is concerned. During the COVID-19 period, South Asian economies have been shattered like the rest of the world. In addition, due to the global impact of the war between Ukraine and Russia, South Asian nations have been suffering too from the oil supply crisis and the grain import issues and so on. An in-depth analysis of the effects of these major issues on the four economies, which carry almost one-third of the world population, especially immediately after the COVID-19 pandemic, certainly has been challenging. Thus, the concluding chapter remains cautious about predicting the second quarter of the 21st century.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.039 | 0.014 |
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".