2015
DOI: 10.1080/17565529.2015.1085362
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Household types as a tool to understand adaptive capacity: case studies from Cambodia, Lao PDR, Bangladesh and India

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Cited by 19 publications
(13 citation statements)
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“…Households with no off-farm income sources were usually the most financially vulnerable to the effect of higher crop variability because they were particularly reliant on agricultural income. These findings are consistent with those of Rurinda et al (2014), Williams et al (2016), andLopez-Ridaura et al (2018).…”
Section: Crop Variabilitysupporting
confidence: 91%
“…Households with no off-farm income sources were usually the most financially vulnerable to the effect of higher crop variability because they were particularly reliant on agricultural income. These findings are consistent with those of Rurinda et al (2014), Williams et al (2016), andLopez-Ridaura et al (2018).…”
Section: Crop Variabilitysupporting
confidence: 91%
“…Historically, land ownership was closely associated with the social groups (caste). In India, the officially recognized social categories include Forward Castes (FC), Backward Castes (BC), Scheduled Castes (SC) and Scheduled Tribes (ST) (Williams et al, 2016). In the study areas, the large and medium landowners mainly belong to the forward castes (Maratha, Rajput) and a small per cent are of de-notified tribes, VJNT (Banjara).…”
Section: Profile Of the Social Groupsmentioning
confidence: 99%
“…The MGNREGA has important implications for how policy might envision and pursue future efforts for pro-poor climate support. To begin with, vulnerably is a multi-faceted phenomenon; no single kind of support is likely to be enough (Fischer & Chhatre, 2015;Williams et al, 2015). While the need to integrate climate vulnerability reduction with broader rural development objectives is by now widely recognized (Ayers & Dodman, 2010;Schipper, 2007), recent scholarship has focused on the potential synergistic effects that may emerge by linking broad-based social protection policies with more specific interventions to target climate risks (Davies et al, 2009;Lemos et al, 2016).…”
Section: Discussionmentioning
confidence: 99%