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Record Nr. |
UNINA9910997189903321 |
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Autore |
Mehta Balwant Singh |
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Titolo |
Predicting Inequality of Opportunity and Poverty in India Using Machine Learning / / by Balwant Singh Mehta, Ravi Srivastava, Siddharth Dhote |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
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ISBN |
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Edizione |
[1st ed. 2025.] |
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Descrizione fisica |
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1 online resource (XXI, 169 p. 42 illus., 37 illus. in color.) |
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Collana |
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India Studies in Business and Economics, , 2198-0020 |
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Disciplina |
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Soggetti |
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Development economics |
Economic policy |
Social policy |
Labor economics |
Development Economics |
Socio-Economic Policy |
Labor Economics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Introduction -- Concept and Measurement of IOp -- Decomposition of Inequality of Opportunity -- Predicting Poverty with Machine Learning and Geospatial Data -- Inequality of Opportunity in Education -- Inequality of Opportunity in Health Care Services -- Conclusion and Way Forward. |
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Sommario/riassunto |
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This open-access book combines traditional economic methods with newer machine learning techniques such as regression trees and random forests to analyse data and provide an in-depth analysis of inequality of opportunity and poverty in India. Using data from national surveys and unique sources like night-time satellite images and location data of points of interest, it explores different aspects of inequality and poverty. The book adopts a unique interdisciplinary approach, blending theories and methods from sociology, economics, geography, anthropology, and computer science to explore three key aspects of human well-being: income, health, and education, focusing on regional disparities. It aims to offer practical insights for policymakers and researchers who want to address social and economic |
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