Gendered Perspectives on Climate Change Adaptation: A Quest for Social Sustainability in Badlagaree Village, Bangladesh

Abstract

Climate change effects cause major socioeconomic challenges for marginalized groups, particularly women, in Bangladesh. Specifically, drought increases resource scarcity, causing social problems that impact women, which can be described as the gendered sociocultural construction of vulnerabilities. Given this constructed dimension of gender-based vulnerability, this paper explores the effects of drought on marginalized women in one local case study, namely Badlagaree village in Gaibandha district, Bangladesh. To examine this linkage, we collected qualitative primary data using ethnographic research methods, primarily focus group discussions. Findings show that gender-based vulnerability is increasing due to growing drought effects, including agricultural production loss. Marginalized women, because of their gender identity, encounter these drought effects through unemployment, food insecurity, illiteracy, early marriage, dowry costs and violence. While further national-scale research is required, this paper argues that in order to overcome such gender-based vulnerability, current development policies, social programs, and adaptation strategies should better recognize such social dynamics. Further, a gender-specific understanding requires incorporation into adaptation policies through greater collaborative governance as an important prerequisite for sustainability.

Extreme events and gender-based violence: a mixed-methods systematic review

“…Although not the focus of this Review, we provide an overview with summary characteristics of the excluded studies exploring the effects of earthquakes, tsunamis, or unspecified natural disasters on GBV (n=26; appendix pp 27-32). Studies were done in more than 40 countries, including: the USA (n=9), [29][30][31][32][33][34][35]42,44 Bangladesh (n=7), 38,41,43,47,52,61,60 India (n=5), 45,48,56,57,59 the Philippines (n=4), 3,8,39,66 Australia (n=3), [63][64][65] Kenya (n=2), 49,58 Belize, 36 Fiji, 67 Haiti, 37 Indonesia, 66 Laos, 66 New Zealand, 40 Pakistan, 46 Peru, 50 Tanzania, 51 Vietnam, 39 and Spain. 62 Four studies included multiple (unspecified) countries in sub-Saharan Africa, Latin America and the Caribbean, and Asia.…”

“…62 Four studies included multiple (unspecified) countries in sub-Saharan Africa, Latin America and the Caribbean, and Asia. 57,[53][54][55] 20 publications were quantitative, [29][30][31][32][33]35,36,44,49,50,51,[53][54][55][56][57]59,[61][62][63] 15 were qualitative, 3,8,34,[37][38][39]42,45,47,48,58,60,64,65,67 and six were mixedmethods. 40,41,43,46,52,66 All quantitative studies were either cross-sectional or ecological, whereas qualitative studies used in-depth interviews (n=15), 3,8,[37][38]...…”

“…after 1999 with the majority published since 2015 (n=25). 3,8,[37][38][39]41,45,46,[48][49][50][52][53][54][55][56][57][58][60][61][62][63][65][66][67] Studies were done from 1989 61 to 2020, 58 although six studies did not state the study period. 36,[45][46][47][48]64 Participant populations ranged from nine girls aged 15-18 years 47…”

“…67 Most studies assessed multiple GBV forms or applied a broad GBV definition. Perpetrators of violence included partners, ex-partners, or husbands (n=30), 3,29,[31][32][33][35][36][37][38][39][40][42][43][44][45][46][48][49][50][53][54][55][56]59,60,[62][63][64][65][66] family members (eg, fathers, uncles, or brother-in-laws; n=13), 3,[36][37][38]41,43,49,52,[57][58][59][60][61] strangers (n=10), 36,38,43,[45][46][47]…”

“…57 The two qualitative studies showed an increase in women's and girls' vulnerabilities during drought including for early marriage and female genital mutilation. 60,58 The four studies located in sub-Saharan Africa found conflicting results. 53,54,55,57 On the basis of Demogrpahic and Health Surveys data from 83 990 women across 19 sub-Saharan African countries, Epstein and colleagues 54 showed that women living in severe drought had higher risks of sexual violence (marginal risk difference 1…”