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Health inequalities: a response to Scambler

2011· letter· en· W2122846155 on OpenAlexaffabout
David Coburn

Bibliographic record

VenueSociology of Health & Illness · 2011
Typeletter
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsUniversity of VictoriaPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsInequalitySociologyMathematics

Abstract

fetched live from OpenAlex

Scambler presents an interesting selective review of the health inequalities literature. I leave to others a critique of his explanatory model. I focus, rather, on his main point: that the basic social structural and political determinants of health inequalities have been neglected. Health inequalities in the developed nations require contextualisation. Today we are faced with a famine in East Africa, not the first, and, unfortunately I believe, not the last. We also live in a world of immense contrasts in wealth and in health between and within nations. While there are high relative inequalities in both wealthy and poor nations, the largest absolute health inequalities occur in the poorer countries. Moreover, in OECD nations SES differences explain only a part of the variance in total health inequalities. Consideration of health inequalities cannot be sharply divided from health trends, since it might be argued that there are health and health inequality trade-offs. Any sociological or epidemiological approach to health trends and health inequalities has to confront the policy-relevant arguments produced by those who argue that economic growth will automatically improve human wellbeing. Or, that many forms of inequality are an unfortunate (or perhaps even necessary) by-product of the more general improvements which can only be brought about by free markets, nationally and internationally. I believe these arguments to be flawed but they are influential and have to be answered. Moreover, regarding health trends, global health levels have been increasing for many decades. In addition, internationally, there has been some convergence among countries in health (dependent on the measure of health used), although that convergence slowed in the 1990s. Interestingly, there is more convergence among nations in health (and in education) than there is in national income. Much of the improvement in health in poor nations is due to the international diffusion of health relevant knowledge and technologies. Health trends and inequalities are produced and reproduced within a more extensive and intensive global capitalist mode of production than ever before. Any consideration of health phenomena thus must surely take into account the influence of the trends, tendencies and contradictions characterising the advanced capitalist mode of production. Analyses which ignore this context miss out crucial policy relevant factors which influence everything within capitalism including the relationships among different factors within capitalism, and risk being captured by single ‘variable’ forms of causal analysis. This follows a general trend in social analysis to try to isolate the ‘independent’ effect of one factor among many interrelated factors, rather than analysing the complex conjunctions of many different facets of social life which form social types or wholes. Within any mode of production those with more power will appropriate more of the social surplus. Power will generally be associated with greater access to assets of whatever kind are valued at the time, and, in the present day, greater access to many kinds of health-related resources and information. Examining the capitalist mode of production over a period of centuries we can discern different historical phases of capitalism and, in the contemporary world, different types of capitalist or market oriented societies, from the remaining welfare state types, through the Anglo-American liberal varieties to such emerging types as China. Analysing different types of society in the modern world, rather than simply the intercorrelations of factors within them, may be a fruitful way of understanding why some nations and societies: (1) have better health than others; (2) display higher or lower levels of income, health (and other) inequalities; (3) show quite different forms of social ‘efficiency’ in translating economic growth into improvements in human wellbeing generally and health in particular. To do this will require more attention to historical and comparative case studies. In any event it would be a mistake to try to ‘over-universalise’ findings across quite different sets of nations. Those low in income in poor countries often spend most of their income on food yet still have a caloric intake not conducive to physical activity. Differences in health within such nations do not have the same causal pathways as in rich nations. The richer nations themselves differ in significant ways, even those apparently quite similar, such as the United States and Canada. But health is just one of many forms of inequality. The lack of ‘real’ as opposed to formal democratic systems in the industrialised world, the existence of a business press rather than a free press, the highly wealth-related differences in the legal system, the immense influence of capital on the political process and on politicians generally, has a great deal to do with the maintenance and reproduction of inequalities, from income, through health, to political participation. Power within capitalism is skewed towards the interests of a dominant class with SES differences partly a consequence of structural class power. Many current problems may be seen as a consequence of the current ‘excessive’ domination of big capital over national and international events. Capital has so much control as to be able to appropriate vast amounts of the social surplus. But there is a contradiction between what is in the interests of an individual enterprise, in driving down wages, for example, and the interests of capital as a whole in actually being able to sell the goods and services produced. Hence, the situation in the United States, and elsewhere, in which corporations (non-financial as well as financial) are awash in cash, trillions of dollars, while the economy languishes because of the lack of consumer demand. Yet, the increasing pressure on the living standards of the lower strata within markets is now being exacerbated because we are told we need more austerity and fewer government services to rescue capital from its own mistakes. More of the same is likely to produce ever more frequent economic crises and a reversal of trends towards greater equality of many kinds within and between nations. Unelected and unrepresentative financial institutions and markets now control the fates of nations regardless of the wishes of their citizens, although facing increasing international and national struggles from those suffering under neo-liberal policies. So, yes, I agree with Scambler that there are too few studies of the structural determinants of health and health inequalities, just as there has been a tendency to avoid confronting the political causes of the social determinants of health. On the other hand, structural analysis too often stays at high levels of abstraction, resulting in comments, such as mine today, with which some might agree but which also require much more specific analytical and practical tools to be policy relevant. In this respect, while I disagree with Richard Wilkinson and his colleagues regarding the central social causality of income inequality regarding health, I certainly do welcome their focusing attention on inequality, on its correlates and consequences (although I would like to see more attention to its causes), and, most of all, actually trying to do something about present degrees of income inequality.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.054
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.031
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.054
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0070.008
Science and technology studies0.0040.017
Scholarly communication0.0140.027
Open science0.0040.008
Research integrity0.0310.036
Insufficient payload (model declined to judge)0.0080.002

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.

Opus teacher head0.078
GPT teacher head0.352
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations4
Published2011
Admission routes2
Has abstractyes

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