Economic Growth, Poverty and Inequality: Update on the Discourse and Lessons for Sri Lanka
Bibliographic record
Abstract
The interplay between economic growth, inequality, and poverty underscores the complexity of development dynamics and the challenge of alleviating poverty. Economic growth is necessary for poverty reduction; however, its adequacy is an issue that has been discussed for about 7 decades. Emphasis on growth promoting policies for reducing poverty fluctuated from time to time depending on the empirical findings. Availability of reliable data and improved computing facilities enabled quantifying the relationship between economic growth and poverty reduction. Many studies in the last decade of the 20th century and first decade of the 21st century confirmed that growth reduced poverty but effect of growth on poverty is heterogenous, hence supplementary policies are necessary to enhance growth effect on poverty. Moreover, the increasing inequality dampen the effect of growth on poverty. Sri Lanka is currently experiencing a crisis driven poverty and achieving higher rate of economic growth is critical for reducing wide-spread poverty.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".