Spatial distribution of SDGS accomplished under MGNREGA beyond SDG1
By: Gupta, Stutee et al
.
Material type: 
BookPublisher: International Journal of Rural Management Description: 19(1), Apr, 2023: p.26-44.Subject(s): SDGS, MGNREGA, SDG1
In:
International Journal of Rural ManagementSummary: Nations across the world share common responsibility towards achieving Sustainable Development Goals (SDGs). To monitor the progress of individual goals and their global-level comparisons, a set of targets and indicators are developed by the experts. However, systematic methods for assessing spatio-temporal progress towards achieving the SDGs are lacking. This study demonstrates the use of geographically referenced information (GIS) analysis in mapping the SDGs as achieved under the Mahatma Gandhi National Rural Employment Generation Act (MGNREGA) programme in India, taking Uttarakhand state as a case study. Geotagged data of assets representing various work categories permissible under MGNREGA are linked to the targets and indicators of various SDGs. Kernel Density Estimation (KDE) function is used to derive spatially explicit maps. Sub-national-level composite analysis of overall contribution of the MGNREGA to SDGs is carried out district wise for better understanding. Results obtained show significant spatial variation in the distribution of works across the districts, reflecting their varying priorities as MGNREGA is a demand-driven scheme. The future implication of the study is a vastly improved ability to derive latent information based on geographical indicators for targeting interventions and developing informed strategies towards SDGs. – Reproduced
https://journals.sagepub.com/doi/abs/10.1177/09730052211037108
| Item type | Current location | Call number | Vol info | Status | Date due | Barcode |
|---|---|---|---|---|---|---|
Articles
|
Indian Institute of Public Administration | 19(1), Apr, 2023: p.26-44 | Available | AR130028 |
Nations across the world share common responsibility towards achieving Sustainable Development Goals (SDGs). To monitor the progress of individual goals and their global-level comparisons, a set of targets and indicators are developed by the experts. However, systematic methods for assessing spatio-temporal progress towards achieving the SDGs are lacking. This study demonstrates the use of geographically referenced information (GIS) analysis in mapping the SDGs as achieved under the Mahatma Gandhi National Rural Employment Generation Act (MGNREGA) programme in India, taking Uttarakhand state as a case study. Geotagged data of assets representing various work categories permissible under MGNREGA are linked to the targets and indicators of various SDGs. Kernel Density Estimation (KDE) function is used to derive spatially explicit maps. Sub-national-level composite analysis of overall contribution of the MGNREGA to SDGs is carried out district wise for better understanding. Results obtained show significant spatial variation in the distribution of works across the districts, reflecting their varying priorities as MGNREGA is a demand-driven scheme. The future implication of the study is a vastly improved ability to derive latent information based on geographical indicators for targeting interventions and developing informed strategies towards SDGs. – Reproduced
https://journals.sagepub.com/doi/abs/10.1177/09730052211037108
There are no comments for this item.