Ryan Cox: Fairness in Education

Most, if not all, systems of education in advanced industrial societies fail to give all participants within them fair chances of achieving certain educational outcomes. They are, in this respect, unfair. What makes them unfair? And what would it take to give all participants a fair chance? According to a standard egalitarian approach—an approach I call the improper influence approach—they are unfair because some differences in educational outcomes within those systems of education are due to differences in things like social class background—things that are illegitimate or improper influences on outcomes. To give all individuals a fair chance, on such an approach, would be to eliminate, or at least mitigate, such influences.

This presentation is about why the improper influence approach is the wrong approach to equality of opportunity, and about why we need a different approach to fairness in education. I point to some difficulties with the improper influence approach and introduce a new approach to fairness in education: the fair chance approach. I argue that the fair chance approach provides a better explanation of what makes systems of education unfair when they are and of what it would take to give all participants within them a fair chance of achieving certain educational outcomes.

Ryan Cox
https://www.sydney.edu.au/arts/about/our-people/academic-staff/ryan-cox.html
Associate Lecturer
Department of Philosophy
University of Sydney

About the Speaker:

I'm a philosopher based at the University of Sydney in the Discipline of Philosophy in the School of Humanities. I am interested in a wide range of philosophical issues, but tend to think and write about issues in political philosophy, the philosophy of mind, and the philosophy of language. In political philosophy, I have published work on educational justice, the relationship between democracy and social equality, and on questions related to political legitimacy and Indigenous justice. In the philosophy of mind, I have published on our knowledge of our own minds and our knowledge of our own reasons for acting and holding particular attitudes. In the philosophy of language, I have published on the syntax and semantics of why-questions.

I have several research projects underway at the moment. One on philosophical issues relating to educational justice; another on the nature of political legitimacy and its application to Indigenous issues; and another on the nature of first-person thought and, more broadly, the role of perspectival thought in the humanities.

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This is a talk with audience Q&A presented by the University of Toronto's Centre for Ethics that is free to attend and open to the public. Free pizza and refreshments will be provided at the event. The talk will also be streamed online with live chat here.

About the Centre for Ethics (http://ethics.utoronto.ca):

The Centre for Ethics is an interdisciplinary centre aimed at advancing research and teaching in the field of ethics, broadly defined. The Centre seeks to bring together the theoretical and practical knowledge of diverse scholars, students, public servants and social leaders in order to increase understanding of the ethical dimensions of individual, social, and political life.

In pursuit of its interdisciplinary mission, the Centre fosters lines of inquiry such as (1) foundations of ethics, which encompasses the history of ethics and core concepts in the philosophical study of ethics; (2) ethics in action, which relates theory to practice in key domains of social life, including bioethics, business ethics, and ethics in the public sphere; and (3) ethics in translation, which draws upon the rich multiculturalism of the City of Toronto and addresses the ethics of multicultural societies, ethical discourse across religious and cultural boundaries, and the ethics of international society.

The Ethics of A.I. Lab at the Centre For Ethics recently appeared on a list of 10 organizations leading the way in ethical A.I.: https://ocean.sagepub.com/blog/10-organizations-leading-the-way-in-ethical-ai