Measuring Inclusive Growth in Developing Countries: Composite Index Approach and Sectoral Transformation Analysis
Why this work is in the frame
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Bibliographic record
Abstract
Inclusive growth is increasingly recognized as being critical to sustainable development, particularly in the context of rising income inequality and social polarization around the globe. Effective policy requires robust measurement, prompting the need to move beyond GDP and supplement traditional economic indicators. This study proposes a novel inclusive growth index (IGI) for 73 developing countries. The index is constructed using factor analysis with principal component analysis (PCA) across four pillars: economy, living conditions, equality, and governance. Our results reveal significant heterogeneity among developing countries, largely driven by variations in economic development and governance. Further analysis using OLS regression explores the impact of sectoral transformation, demonstrating a statistically significant positive relationship between shifts from the agricultural to the service sector and the IGI. These findings provide valuable insights for policymakers seeking to create more opportunities and target interventions to achieve more inclusive growth in developing economies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it