Identification of backward district in India by applying the principal component analysis and fuzzy approach: A census based study

Basu, Tirthankar

doi:10.1016/j.seps.2020.100915

Cited by 15 publications

(9 citation statements)

References 21 publications

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“…to make better understand the nature of backwardness in light of geographical locations (Paul et al 2021). In contrast to Chang et al (2015) and Bergstrand et al (2015), this study has been characterized along with specific indicators of social vulnerability and hence in this study researchers follow the selection criteria as given by Islam and Hasan (2015), Emmanuel et al (2017) and Basu and Das (2020). A wide range of factors make an impact for the backwardness in this deltaic part of West Bengal.…”

Section: Discussionmentioning

confidence: 99%

“…Overall literacy gap among the male-female and literacy level of the female population make more reluctant to address the real ground situation. Bakshi et al (2015) and Basu and Das (2020) have tried to frame backwardness at district level for Indian states where as NITI Aayog in 2017 also developed the methodology to addressed the backwardness and evaluated 115 districts as backward applying 11 indicators. Hence in this research, we have tried to develop the level of demographic and socio-economic backwardness taking the high and very high PCA values (taking PCA 1 to PCA 5) for framing the The characteristics of categories 1 and 2 are depicted in this analysis from numerous demographic and socioeconomic perspectives.…”

Section: Discussionmentioning

confidence: 99%

“…inland and riverine/ estuarine) for proper adaptation and methodology. This research has been conducted by taking into account a group of indicators under five components that are related to various facets of quality of life and regional backwardness (Basu and Das 2020). Through the identification of high to very high backward villages, it has exposed some significant facts.…”

Section: Conclusion and Policy Recommendationmentioning

confidence: 99%

“…Anyway association with hazards whether it is ordinary or manufactured is a normal issue. Hazard is along these lines seen as the fiasco situation, wherein some threat of disaster exists considering the way that the human people has set itself in condition of shortcoming (Hahn et al 2009 ;Basu and Das 2020). Is it simply the natural perils winning there, or the impacts of ordinary dangers on the people which is disclosing the overall helplessness?…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Socio-demographic backwardness in cyclone prone coastal villages: An Insight from Indian Sundarban

Mondal

Haldar

Biswas

et al. 2022

Saf. Extreme Environ.

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The capability to design for, respond to, and recover from natural hazards is much influenced by demographic and socio-economic vulnerability of the region. Triggering effect of cyclone induced multi-hazards in the coastal areas of West Bengal, India makes the life and livelihood of people miserable. Very recent cyclones, like, Fani, Bulbul, Amphan and Yaas make people much more susceptible to hazard with the evil impact of on-going pandemic. According to IPCC, sensitivity and adaptive capacity analysis at micro level is taking much importance to address the readiness situation of the region. In this backdrop, the study aims to assess and map the level of demographic and socio-economic backwardness at village level for Kakdwip coastal area under coastal West Bengal, India. Applying principal component analysis we have tried to find out the level of demographic and socio-economic backwardness at different geographical locations (categorise as inland, riverine/ estuarine, coastal and island). The final findings suggest that backwardness is more prevalent in the southern part of the research region, with island and riverine/ estuary villages being particularly vulnerable. When the results have tries to find out the triggering factors at different geographical locations, female and child population, land holdings and earning of household came as the dominant factors for such higher degree of backwardness. These findings, when combined with micro level assessments, could help village administrators, planners and policymakers, and emergency managers design more effective and spatially tailored backwardness management plans.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Conclusion and Policy Recommendationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Socio-demographic backwardness in cyclone prone coastal villages: An Insight from Indian Sundarban

Mondal

Haldar

Biswas

et al. 2022

Saf. Extreme Environ.

View full text Add to dashboard Cite

show abstract

“…Identifying poor households and vulnerable groups has been an important research area for development economists and social scientists (1)(2)(3)(4)(5)(6) . This has gained importance, especially in India, as policy planners look at ways to prevent leakages and figure out ways to efficiently roll out programs for the needy.…”

Section: Introductionmentioning

confidence: 99%

Measuring the economic status of different caste groups in rural India: An application of principal component analysis

Manaloor¹,

Radhakrishnan²,

Raghu³

et al. 2021

IJED

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Background/Objectives: To prevent leakages and to efficiently roll out development programs, it is important that policy-makers and researchers are able to identify poor households that need intervention. Such identification will aid in adopting a targeted approach for poverty reduction strategies and improvement of livelihoods. Methods/Statistical analysis: The present study conducted amongst 3845 farm households in three agro-biodiversity hotspot regions in India, uses non-money metrics method to measure household economic status. Principal component analysis is used to build an asset index score of each household and determine the economic grouping based on caste categories. Findings: The results show a high level of inter-regional differentiation among the household economic status and intra-sub caste groups. The overall economic status reveals that Meenangadi falls in the 'rich/richest' group compared to the Kolli Hills in the 'middle' group and Koraput in the 'poorest' group. Our results are also important for household classification based on the social stratification within a regional context. Hence, it is reasonable to state that the asset based method is relevant for fine tuning identification of marginalized communities, notably in the deprivation hotspots, paving the path for their inclusive growth. Novelty/Applications: The present study attempts not only to identify economic status of rural households in different states of India, but also looked at the economic status of different castes, particularly at scheduled tribe groups that are dominant in the study area.

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Assessing the vulnerability trifecta: species, climate, and anthropogenic pressures on protected areas of the Central Indian Highlands

Singh,

Moharir

2023

J Wildl Manag

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Efficient management of protected areas (PAs) is important to ensure conservation and long‐term sustenance of threatened species. It is therefore essential to understand the vulnerability of PAs in a multi‐pronged approach by considering the cumulative effects of species, climatic, and anthropogenic attributes. We assessed the overall vulnerability of PAs in the Central Indian Highlands (CIH), which is a landscape of high biodiversity value. Over 81% of PAs experienced medium to high vulnerability due to anthropogenic pressures, and 68.75% of PAs faced medium to high vulnerability due to climate change and conservation status of species within the PA. Our categorization of PAs revealed that 50% of PAs were vulnerable to all 3 attributes. Further, there was a strong correlation between species and anthropogenic vulnerability indices in the PAs of the CIH landscape. Our results may help local policy makers in prioritizing the optimal and cost‐effective conservation management of existing PAs, which can be extended for cost‐effectiveness and efficient resource allocation of PAs, through this multipronged approach, beyond the CIH landscape.

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Identification of backward district in India by applying the principal component analysis and fuzzy approach: A census based study

Cited by 15 publications

References 21 publications

Socio-demographic backwardness in cyclone prone coastal villages: An Insight from Indian Sundarban

Socio-demographic backwardness in cyclone prone coastal villages: An Insight from Indian Sundarban

Measuring the economic status of different caste groups in rural India: An application of principal component analysis

Assessing the vulnerability trifecta: species, climate, and anthropogenic pressures on protected areas of the Central Indian Highlands

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