Introduction: Philosophical Perspectives on Education for Well-Being
Bibliographic record
Abstract
This special issue of Paideusis focuses on "Philosophical Perspectives on Education for Well-Being."Well-being as a social and political concern -sometimes under the term "happiness" -has been put into greater spotlight in public discourse and public policy in recent years (e.g., Bok, 2010;Rose & Rowlands, 2010;Stiglitz, Sen, & Fitoussi, 2010), and a number of assessment tools to measure human well-being/quality of life have been developed at national and international levels, like the UN's Human Development Index, the OECD's Better Life Index, and the New Economics Foundation's Happy Planet Index.For the last few years the Canadian Index of Wellbeing (CIW) has been used to measure well-being of Canadians to provide a measure of social progress as alternative or complement to the sole economic measure of GDP (CIW, 2012).Different academic disciplines have been contributing to the discourse on human well-being, including philosophy (e.g., Aristotle, trans.1976;Griffin, 1986;Sumner, 1996), psychology (e.g., Diener, 1984; Kahneman, Diener, & Schwarz, 1999;Seligman, 2011), and economics (Frey, 2008;Jackson, 2009;Layard, 2005), and a range of conceptualizations of well-being have been proposed (for a structured overview of Western approaches to well-being, see Falkenberg, 2014).Judging by my observation of the North American public discourse on well-being, approaches to well-being that have led to empirical studies with reportable "findings" on well-being, like those linked to positive psychology (e.g., Lopez & Snyder, 2009), seem to have exerted much greater influence on public discourse and public policy concerning the school system than those that do not.Philosophy has probably the longest tradition of all disciplines in dealing with the concept of well-being, providing a range of different conceptualizations (e.g., Griffin, 1986; Talbott, 2010), albeit sometimes under the use of a different term, like happiness (Almeder, 2000), the good life (Feldman, 2004), and welfare (Sumner, 1996).Philosophical perspectives on well-being seem to have a declining impact on public discourse, and this is mirrored in the declining role of philosophy of education in teacher education and education more generally (Clark, 2006), and in Canada in particular (Christou & Bullock, 2013;Vokey, 2006).In education, a discourse has been building that gives privilege to the idea that educational practice should be guided by research that shows "what works" (for a critique of this discourse, see Biesta, 2007Biesta, , 2010)).There is, however, one philosophical perspective on well-being that has been quite influential at the policy level: the Capabilities Approach.This approach to well-being has been developed by Armartya Sen (e.g., 1993, 2009) and Martha Nussbaum (e.g., 2000, 2011).Sen was a consultant on the creation of the very prominent Human Development Index of the United Nations (Saito, 2003, p. 22), and he was also a member of the Commission on the Measure of Economic Performance and Social Progress in France, established by former French President Nicolas Sarkozy for the purpose of considering the limitations of GDP as a measure of social progress and the feasibility of alternative assessment tools (Stiglitz, Sen, & Fitoussi, 2010).I want to use the Capabilities Approach to well-being to illustrate one way in which philosophical perspectives can contribute and, in the case of the Capabilities Approach, have actually
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.027 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".