Resumen

EGLASH, Ron et al. A mathematical tool kit for generative justice. ETD [online]. 2017, vol.19, n.3, pp.761-785. ISSN 1676-2592.  https://doi.org/10.20396/etd.v19i3.8648374.

How can mathematics best contribute to social justice and sustainability? Distributive justice addresses poverty and related problems from the top down: by moving extracted value from private to state ownership. But, the history of bureaucratic socialism, from the pollution in the USSR to food shortages in Venezuela, shows just as many problems as capitalism. Generative justice, in contrast, works from the bottom up: replacing value extraction and alienation with value circulation. These generative cycles include unalienated labor, such as that we find in makerspaces and open source; unalienated ecological value such as organic farming, and unalienated expressive value such as sexual diversity, liberated arts, and other polysemic freedoms. This essay will review 3 aspects of ethnosciences (ethnomathematics, ethnocomputing and related disciplines) in relation to generative justice. In the case of indigenous knowledge systems, there is a danger of alienation of value as concepts are translated into models, and further abstracted into classroom curricula. In the case of vernacular knowledge systems, colonization by commercial interests has already occurred, and the challenge is to develop a decolonized alternative. Finally, in the case of school-community relations, a full generative cycle can incorporate economic, health and environmental flows of value by leveraging these generative STEM approaches. This essay will provide both theory and some initial results of this generative STEM approach to a more just and sustainable world.

Palabras clave : Ethnocomputing; Generative Justice; Self-Organization; Nonlinear Dynamics; Indigenous; Ethnomathematics.