Privilégio, poder e performatividade: a ética da matemática na sociedade e na educação
DOI:
https://doi.org/10.37853/pqe.e202103Resumo
Os benefícios indiscutíveis e as virtudes intrínsecas da matemática não deveriam provocar uma cegueira quanto ao possível dano colateral provocado pela sua imensa, impiedosa e destrutiva força**, que é capaz de fazer a educação e a sociedade se renderem em direção a um futuro reformulado. Por causa do grande poder da matemática e da sua influência por toda a sociedade, é preciso realizar uma auditoria ética. Este artigo conduz uma crítica ética considerando quatro aspectos inter-relacionados da matemática na educação e na sociedade e seus impactos negativos. O primeiro deles é a supervalorização da matemática e os efeitos que este poder tem em manter privilégios; em seguida, os poderosos impactos negativos que estudar matemática têm em muitos estudantes de modo individual; terceiro: as aplicações visíveis, porém problemáticas, da matemática dentro da sociedade, as quais são protegidas de críticas porque a matemática continua a ser vista como neutra; o último aspecto é os efeitos profundos e performáticos das aplicações ocultas da matemática reformatadoras da sociedade e modificadoras da vida cotidiana, mas mantidas sem verificação em qualquer sentido. A maior parte deste artigo é dedicada a revelar estes efeitos prejudiciais. As soluções propostas que estão aqui servem para fomentar a consciência ética no estudo de matemática em todos os níveis e também para desafiar o estereótipo generalizado da matemática como algo eticamente neutro.
Palavras-chave: Matemática. Ética. Poder. Sociedade.
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Abtahi, Y., Gøtze, P. Steffensen, L. Hauge, K. H. and Barwell, B. (2017). Teaching Climate Change in Mathematics Classrooms: An Ethical Responsibility, The Philosophy of Mathematics Education Journal, No. 32. http://socialsciences.exeter.ac.uk/education/research/centres/stem/publications/pmej/pome32/index.html. Accessed 10 August 2019.
Allchin, D. (2004). Should the Sociology of Science Be Rated X? Science Education, Vol. 88, No. 6; pp. 934-946.
Bakan, J. (2004). The Corporation. London: Constable.
BBC News (2013). 'Dangerous' financial products named, 15 March 2013. https://www.bbc.co.uk/news/business-21760855. Accessed 21 August 2018.
Becker, H. (1963). Outsiders, Oxford: Free Press.
Beer, D. (2016). Metric Power, London: Palgrave Macmillan.
Berman, E. and Hirschman, D. (2018). The Sociology of Quantification: Where Are We Now? Contemporary Sociology, Vol. 47, No. 3; pp. 257 - 266.
Bourdieu, P. (1986). The Forms of Capital. J. G. Richardson (Ed.). Handbook of Theory and Research for the Sociology of Education. New York: Greenwood press. pp. 241-258.
Boylan, M. & Coles, A. (2017). Is Another Mathematics Education Possible? An Introduction To a Special Issue on Mathematics Education and the Living World: Responses to Ecological Crisis, The Philosophy of Mathematics Education Journal, No. 32. http://socialsciences.exeter.ac.uk/education/research/centres/stem/publications/pmej/pome32/index.html. Accessed 10 August 2019.
Brown, W. (2015). Undoing the Demos: Neoliberalism’s Stealth Revolution. New York: Zone Books.
Buerk, D. (1982). An experience with some able women who avoid mathematics. For the Learning of Mathematics. Vol. 3, No. 2; pp. 19-24.
Buxton, L. (1981). Do you Panic about Maths? Coping with Maths Anxiety. London: Heinemann Educational Books.
Calıskan, K (2010). Market threads: how cotton farmers and traders create a global commodity. Princeton, New Jersey: Princeton University Press.
D’Ambrosio, U. (2007). Peace, Social Justice and Ethnomathematics. The Montana Mathematics Enthusiast, Monograph 1, 2007; pp. 25-34.
Davies, W. (2017). The Limits of Neoliberalism Authority, Sovereignty and the Logic of Competition. Thousand Oaks, California: SAGE Publications.
De Mesquita, E. B. (2019). Economics After Neoliberalism - Quantification shapes how we think about public policy—often for the worse. Boston Review, Summer 2019 Issue. http://bostonreview.net/forum/economics-after-neoliberalism/ethan-bueno-de-mesquita-perils-quantification. Accessed 15 August 2019.
EiM (no date). The Cambridge University Ethics in Mathematics Project. https://ethics.maths.cam.ac.uk/. Accessed 24 July 2019.
Ernest, P. (1988). The Attitudes and Practices of Student Teachers of Primary School Mathematics, Proceedings of 12th International Psychology of Mathematics Education Conference, Veszprem, Hungary: OOK, Vol. 1; pp. 288-295.
Ernest, P. (1991). The Philosophy of Mathematics Education. London: Routledge.
Ernest, P. (2010) Why teach mathematics? Professional Educator, Vol. 9, No. 2 (June 2010) pp. 43-47. https://cld.pt/dl/download/c8a79c90-1ce5-44a8-85fe-f060968e1dd4/biblioteca%20MATEAS/edu%20mat/why%20teach%20math.pdf. Accessed 18 November 2019.
Ernest, P. (2011). Mathematics and Special Educational Needs. Saarbrucken, Germany: Lambert Academic Publishing.
Ernest, P. (2018). The Ethics of Mathematics: Is Mathematics Harmful?. In P. Ernest (Ed.). The Philosophy of Mathematics Education Today. Switzerland: Springer, 2018.
Ernest, P. (in press). Mathematics, Ethics and Purism: An application of MacIntyre’s virtue theory. Forthcoming in Synthese, special issue on Virtue Theory of Mathematical Practices. Guest Editors: Andrew Aberdein, Colin Jakob Rittberg, Fenner Stanley Tanswell.
Evans, J. (2000). Mathematical Thinking and Emotions in Context: Adults, Practices and Numeracy, London: Routledge.
Fineman, S. (2004). Getting the Measure of Emotion - and the Cautionary Tale of Emotional Intelligence. Human Relations, Vol. 57; pp. 719-740.
Foucault, M. (1976). Discipline and Punish, Harmondsworth: Penguin.
Foucault, M. (1980). Power/Knowledge (edited by C. Gordon), New York: Pantheon Books.
Gardner, H. (1983). Frames of Mind: The Theory of Multiple Intelligences. New York. Basic Books.
Gorur, R. (2016). Seeing like PISA: A cautionary tale about the performativity of international assessments. European Educational Research Journal, Vol. 15, No. 5; pp. 598-616.
Gould, S. J. (1981). The Mismeasure of Man. New York: W.W. Norton.
Hayek, F. A. (1948). The use of knowledge in society. Individualism and the economic order. Chicago: Chicago University Press, pp. 77-91.
Kellert, S. R. & Wilson, E. O., Eds., (1995) The Biophilia Hypothesis. Washington, DC, USA: Island Press - A Shearwater book.
Kelman, H. C. (1973). Violence without moral restraint: reflections on the dehumanization of victims and victimizers. Journal of Social Issues, Vol. 29, No. 4; pp. 25-62.
Lewis, M. (2019). Fit for purpose… Are we tracking our lives a fitbit too far. The Observer newspaper, UK. Sunday 10 November 2019, p. 50/
Marjanovic, O., Cecez-Kecmanovic, D. & Vidgen, R. (2018). Algorithmic Pollution: Understanding and Responding to Negative Consequences of Algorithmic Decision-Making. U. Schultze, M. Aanestad, M. Mähring, C. Østerlund, & K. Riemer, Eds. Living with Monsters? Social Implications of Algorithmic Phenomena, Hybrid Agency, and the Performativity of Technology. Switzerland: Springer, 2018; p 31-47.
Maxwell, J. (1989). Mathephobia. P. Ernest, Ed., Mathematics Teaching: The State of the Art. London: Falmer Press; pp. 221-226.
Mennicken, A. & Espeland, W. N. (2019). What’s New with Numbers? Sociological Approaches to the Study of Quantification. Annual Review of Sociology. Vol. 45, No. 24; pp. 1–23.
Monbiot, G. (2017). Neoliberalism – the ideology at the root of all our problems. The Guardian, 15 April 2016. https://www.theguardian.com/books/2016/apr/15/neoliberalism-ideology-problem-george-monbiot. Accessed 5 August 2019 (revised version).
Mutodi, P and Ngirande, H. (2014). The Influence of Students` Perceptions on Mathematics Performance. Mediterranean Journal of Social Sciences, Vol. 5, No. 3; pp. 431-445.
National Numeracy (2015) The debate about a ‘maths gene’. https://www.nationalnumeracy.org.uk/research-debate-about-maths-gene. Accessed 19 November 2019.
O’Neil, C. (2016). Weapons of math destruction: How big date increase inequality and threatens democracy. New York, NY: Broadway books.
Orwell, G. (1949). Nineteen Eighty-Four: A Novel. London: Secker & Warburg.
Power, M. (1999). The Audit Society = Rituals of Verification. Oxford: Oxford University Press.
Radical Statistics group (n. d.). About Us. http://www.radstats.org.uk/about-radical-statistics/. Accessed 3 August 2017.
Raudenbush, S. W. (1984). Magnitude of teacher expectancy effects on pupil IQ as a function of the credibility of expectancy induction: A synthesis of findings from 18 experiments. Journal of Educational Psychology, Vol. 76, No. 1; pp. 85–97.
Rosenthal, R. and Jacobson, L. (1968). Pygmalion in the Classroom. New York, USA: Holt, Rinehart and Winston.
Russell, B., and Einstein, A. (1955). The Russell-Einstein Manifesto. http://www.pugwash.org/about/manifesto.htm. Accessed 23 April 2015.
Sells, L. W. (1978). Mathematics - Critical Filter. The Science Teacher, 1978 (February); pp. 28-29.
Sisk, V. F., Burgoyne, A. P., Sun, J., Butler, J. L., & Macnamara, B. N. (2018). To what extent and under which circumstances are growth mind-sets important to academic achievement? Two meta-analyses. Psychological Science, Vol. 29, No. 4; pp. 549-571.
Skovsmose, O. and Ravn, O. (2019). Connecting Humans to Equations - A Reinterpretation of the Philosophy of Mathematics. Switzerland: Springer Nature.
Skovsmose, O. Ed, (2014). Critique as Uncertainty. Charlotte, NC, USA: Information Age Publishing.
von Mises, L. (1978). Epistemological Problems of Economics. New York, USA: New York University Press. (First published in German in 1933).
West, J. (2012). Ethics and Quantitative Finance, Griffith Business School, Australia. from https://www120.secure.griffith.edu.au/research/file/7b01820e-e28a-490f-b698-5c6ec507c9a2/1/2012-04-ethics-and-quantitative-finance.pdf. Accessed 30 August 2018.
Wikipedia (2019). Bildung. https://en.wikipedia.org/wiki/Bildung. Accessed 18 November 2019.
Zevenbergen, R. (1998). Language, mathematics and social disadvantage: a Bourdieuian analysis of cultural capital in mathematics education. http://www.merga.net.au/documents/RP_Zevenbergen_1_1998.pdf. Accessed 3 May 2015.
