Intersecting Inequalities: Climate Change, Migration, and Gendered Vulnerability in Northern Kenya’s ASALs
Keywords:
ASALs, climate change, gendered vulnerability, migration, Northern KenyaAbstract
This study examines how climate-induced migration interacts with existing social inequalities to produce differentiated gendered vulnerability outcomes among pastoralist and agro-pastoralist communities in Marsabit, Turkana, and Wajir counties of Northern Kenya’s Arid and Semi-Arid Lands (ASALs). Guided by Feminist Political Ecology and Intersectionality Theory, the study analyses how gender intersects with four axes of social differentiation to produce distinct vulnerability and adaptation profiles. Feminist Political Ecology frames the analysis of gendered resource access and multi-scalar power dynamics, while Intersectionality theory enables disaggregation of vulnerability across overlapping social positions. The study employed a concurrent mixed-methods design over a 12-month fieldwork period (2024 to 2025), comprising a stratified random sample of 720 household survey respondents (240 per county), 18 focus group discussions, 45 life-history interviews, 30 key informant interviews, and sustained participant observation. Qualitative data were thematically analysed in NVivo and triangulated against survey findings. Key findings revealed that male labour migration, reported by 68 per cent of households as the primary coping strategy, increased women’s caregiving burden by an average of 4.2 hours per day and reduced economic security by 41 per cent in female-headed households, and elevated exposure to gender-based violence. The study concludes that climate change and migration systematically amplify pre-existing intersectional inequalities while creating adaptive opportunities that remain disproportionately accessible to those with greater social and educational capital. It recommends gender-responsive climate policies, expanded access to productive resources for women, livelihood diversification programmes, and integration of indigenous knowledge into community-based early warning systems.

