Role of Macro-Economics in Minimizing Obstacles to Sustainable Development (Islamic Perspective)
Bibliographic record
Abstract
Economic development occupies a significant status is Islam, as Muslims are commanded to settle and advance the earth. Since anything required to perform a duty is a duty itself, settling the earth can be achieved only by development, which can be achieved by production. The latter builds the earth and assists man in worshipping God.The present paper concentrates on the role of macroeconomics in accomplishing economic development from an Islamic perspective. The Noble Qur’an verses and Hadith traditions are reported from specialists in a bid to provide the sought complete picture.Section One investigates the capitalistic view to solve economic crises, which represent the major obstacle to any stage of development. Section Two defines economic development from an Islamic perspective, as well as the criteria set to solve relevant problems. Section Three explores the obstacles to sustainable development in the Islamic World and proposes solutions to alleviate them.This brief study sheds light on the Islamic approach to (sustainable) development, showing the resulting public economic welfare, which would be definitely reflected on individual well-being.The major conclusion that sustainable development is a comprehensive concept associated with the continuity of economic, Poverty and unemployment are the most crucial obstacles that hinder sustainable 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".