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Analysing and modelling wellbeing: psychological, bodily, social, and environmental dimensions Neil Thin School of Social and Political Science University of Edinburgh. Main messages. Wellbeing is ineffable: statistical reports don’t make the uncertainties disappear .
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Analysing and modelling wellbeing: psychological, bodily, social, and environmental dimensions Neil Thin School of Social and Political Science University of Edinburgh
Main messages • Wellbeing is ineffable: statistical reports don’t make the uncertainties disappear. • With or without stats, the ‘wellbeing’ rubric helpfully tilts policy conversations towards positivity and ultimate values • The ‘happiness lens’ adds: empathy;holism; and narrativity - but only if we transcend numerical reductionism. • It also helps to consider implicit and explicit models, visualizations, and analytical frameworks.
Francis Hutcheson1694-1746What matters is ‘the greatest happiness for the greatest numbers’
John Sinclair(1754-1835)Coined the term ‘statistics’;governments should assess the ‘quantum of happiness’
Samuel Smiles(1812-1904)Sparked the mass-market ‘self-help’ movement
Where does wellbeing occur? Where are the causes? Where can/should policies make a difference?
Commissioned by UK DFID and World Bank for UN conference on Sustainable Development, Johannesburg 2002 Fights back against pathologism and residualism in social monitoring Positive social qualities: justice, solidarity, participation, security Policy Press, Bristol Part One: Introductory overview and critique of happiness in policy discourse and research Part Two explores actual and potential applications of “happiness” in various policy domains: intimacy; parenting; schooling; gender reform; old age; workplace; business.
A dynamic and interpretive AIEOU model of happiness Interpretation Anticipation Experience Outcomes Unpleasantness
Wellbeing assessment takes us ‘beyond GDP’ and ‘beyond profit’.Good, but what if pathological numerophilia is the problem?
Why is measurement neurosis dangerous? ‘Statistics’ has been reduced to numerical data; this is bad science What matters is what matters (forget ‘what can’t be counted doesn’t count’). Happiness and social progress are elusive and uncertain: we need mixed learning methods, because numerical proxies are distortive.
Another warning about stats: Subjective ‘data’ aren’t just ‘given’ facts: they might be better termed ‘elicitata’ To interpret any human-response survey, we need to know about the context and process of elicitation E.g. how did Oxfam Scotland end up weighting ‘feeling good’ self-reports as the least important evidence of wellbeing? (weighted less than one-fifth of the importance of housing satisfaction! One-third of the importance of money?)
Positive Social Planning • Be assertively positive about social goods • Develop analytical tools, concepts, and approaches for envisioning and planning really good societies Beyond GDP, beyond measurement (avoid economism and statistical reductionism, promote robust qualitative assessment)
Four SQ domains (Thin, 2002) • social justice(equal opportunity, fair and transparent rewards, procedural justice, rights and duties) • solidarity(cohesion, empathy, co-operation, and associational life) • participation(opportunities for meaningful engagement) • security(job security, physical safety, trust in colleagues and management)
models and visual metaphors of personal and social value A 20 x 20 Pecha Kucha show
Wellbeing Wales: a ‘wellbeing’ variant of the 3 pillars SD model
Urie Bronfenbrenner’s systems model of development Bronfenbrenner, Urie (1979) The Ecology of Human Development: Experiments by Nature and Design. Cambridge, MA: Harvard University Press
Maslow’s ‘hierarchy of needs’ diagram Urie Bronfenbrenner. (1979). The Ecology of Human Development. Cambridge, MA: Harvard University Press.