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Animals in Disaster Social Work: An Intersectional Green Perspective Inclusive of Species

AbstractDisasters do not just affect humans. And humans do not only live with, care for or interact with other humans. In this conceptual article, we explain how animals are relevant to green and disaster social work. Power, oppression and politics are our themes. We start the discussion by defining disasters and providing examples of how three categories of animals are affected by disasters, including in the current COVID-19 pandemic. They are: companion animals (pets), farmed animals (livestock) and free-living animals (wildlife), all of whom we classify as oppressed populations. Intersectional feminist, de-colonising and green social work ideas are discussed in relation to disaster social work. We argue that social work needs to include nonhuman animals in its consideration of person-in-environment, and offer an expanded version of feminist intersectionality inclusive of species as a way forward.
- Queensland University of Technology Australia
- Flinders University Australia
- Flinders University Australia
- University of Canterbury New Zealand
- Seventh-day Adventist College of Education Ghana
577, disasters, 300, animals, climate change, Alliances, intersectionality
577, disasters, 300, animals, climate change, Alliances, intersectionality
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).5 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
