Causality between Regional Economic Independence and Decentralization on Poverty Alleviation and Community Welfare Mediated by Economic Development
Bibliographic record
Abstract
Poverty and welfare are concrete problems that do not end, especially in developing and poor countries. The East Kalimantan Province, which contributes the most to Indonesia’s natural wealth, has actually experienced economic and social degradation. This study has the ambition to identify the causality between regional economic independence, decentralization, and regional economic development on poverty alleviation and community welfare in East Kalimantan Province during the 2013-2018 period. Panel data collected from nine objects, then interpreted with Structural Equation Modeling (SEM) technique as an empirical approach to test ten hypotheses. WarpPLS software applied to interpret the data. There are eight findings that are in line with the hypothesis, where regional economic independence has a positive-significant effect on regional economic development, but in fact it has a negative-significant effect on poverty alleviation. Regional economic development has a negative-significant effect on poverty alleviation, but it has a positive-significant effect on community welfare. Regional economic development has mediated the relationship between regional economic independence and decentralization on poverty alleviation and community welfare. In addition, poverty alleviation has a significant negative effect on community welfare, but has mediated the relationship between regional economic development and community welfare. Two conclusions in the new findings are in sharp focus because they contradict the hypothesis, namely that decentralization has a significant negative effect on regional economic development and community welfare. Practical and theoretical contributions apply to reveal the linkages between economic aspects of local development to support sustainability. The refinement of methods, data, variables, and analytical techniques is an important note for the follow-up agenda.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".