Our Original Questions
Q1. You claim to present an overview of the research on health and inequality, yet leave out the scientifically most heavyweight survey of the field, Princeton Professor Angus Deaton’s article in the prestigious Journal of Economic Literature. Is this simply because Deaton finds no robust relationship between life expectancy and income inequality among the rich countries? (Deaton, A. S. ‘Health, inequality and economic development’, Journal of Economic Literature, May 2001)
Q2. You base much of your thesis on the relationship between inequality and life expectancy within U.S states. Why do you neglect to tell your audience that researchers have found that this relationship vanishes once they control for demographic differences? (Deaton, A.S., D. Lubotsky. “Mortality, inequality and race in American cities and states”, Social Science & Medicine, March 2003)
Response from Wilkinson and Pickett (Wilkinson and Pickett)
Angus Deaton’s 2001 study is far from being the most up-to-date review of inequality and health and the social determinants of health has never been his main field. Look also at more recent work, perhaps particularly from the group at the Harvard School of Public Health, many of which are co-authored by I Kawachi, Professor of Social Epidemiology and Chair of the Department of Society, Human Development, and Health at Harvard (see for instance reviews such as Kondo N, Sembajwe G, Kawachi I, van Dam RM, Subramanian SV, Yamagata Z. Income inequality, mortality, and self rated health: a meta-analysis of multilevel studies. British Medical Journal 2009:339).
In 2006, we published a much more comprehensive review than Deaton’s, taking into account the five years of research published since his 2001 paper, and based on close to 200 studies. Other ‘heavyweight’ economists, including Nobel laureates, have also written about the significance of inequality for wellbeing and human capital formation. Since Deaton’s paper several of the issues he raised have been the subject of further research, including the idea that the relationship between inequality and health in the 50 states is actually attributable to the proportion of each state’s population which is African-American. The same point was once raised in relation to the pattern of violence among the states. Both have now been shown to be inaccurate. (See 38-41. We hope the TaxPayers' Alliance will inform their readers of these more recent findings to avoid further misunderstanding.)
The reason why the initial confusion over the role of ethnicity arose is because in those states where there is a larger African American population there is also a bigger income gap between blacks and whites. But in the states with a higher proportion of African Americans it is not only black health which is worse: white health is also poorer. The issue is not of course that skin colour determines health. Instead, ethnicity matters when skin colour becomes a marker of social status which attracts the same discrimination and downward prejudice that low social status and deprivation have always attracted. The evidence on violence is similar. Relations between inequality and violence exist in both Southern and Northern states. Rates of homicide perpetrated by white men are related to income inequality even when inequality is measured only among whites. To suggest removing or controlling for the proportion of the population which is African American in each state is analogous to saying one should look at the effects of inequality only after taking out the disadvantaged.
We do not of course base our thesis on a single relationship between inequality and life expectancy within US states. Given that there are now over 200 studies testing this relationship there is no possible reason for doing so.
Wilkinson and Picket write in response to our critique that a causal link between inequality and health has not been established, that "other ‘heavyweight’ economists, including Nobel laureates, have also written about the significance of inequality for well-being and human capital formation".
Their response contains a reference to the work of Nobel prize winner James Heckman. The reader is given the impression that Heckman's work contains evidence supporting Wilkinson and Picket.
However Heckman's paper contains nothing of the kind. The study investigates the effect of low self income on cognitive and non-cognitive abilities, not the effect of inequality. There is thus zero evidence in this paper (or anywhere else in professor Heckman's seminal work) supporting Wilkinson and Pickets claim that other people’s income reduce your health.
Note than Wilkinson and Pickett's choice of words. They write that Heckman has "written" about inequality and health, which is of course technically true. But what they don't tell the readers is that while he has indeed written about these variables, he has not found any evidence supporting the claims of Wilkinson and Pickett. It is becoming increasingly tiresome to point this out, but Wilkinson and Pickett again and again engage in extraordinary acts of dishonesty.
We do not typically like referring to authority as a way to end an argument. However, Wilkinson and Pickett are attempting to deceive the general public by giving the impression that their claims represents scientific consensus, whereas they are in fact directly in contradiction with the consensus scientific view.
The gold standard article about income inequality and Health was written by Angus Deaton, and concluded that no causal relationship has been established between inequality and life expectancy. Yet in the popularization of research for the broad public, Wilkinson and Pickett made the astonishing choice on never citing or acknowledging the existence of this study.
When pushed, Wilkinson (University of Nottingham) and Pickett (University of York) dismiss Angus Deaton (Princeton University) as not competent to make judgement on the "social determinants of health".
Deaton's article was published in the Journal of Economic Literature [JEL], the most authoritative journal in economics for review articles. One of the purposes of this journal is to invite scholars that rest of the field consider one of the prime experts in a given field to summarize the view of profession.
Wilkinson and Pickett may not consider Deaton enough of an expert to discuss the relationship between income inequality and health, but the economic profession obviously did, in that Deaton was invited to write the overview article about "Health, inequality, and economic development" in the JEL.
Deaton's article as of now has more than 5 times as many impact-factor weighted citations as Wilkinson and Pickett's own review article. Wilkinson and Pickett may not consider Deaton an expert, but the scientific community clearly does.
Who then should we trust, the academic judgement of the profession or the personal opinion of Wilkinson and Pickett? We will let our readers decide themselves... Wilkinson and Pickett secondly claim that Deaton's study (published in 2003) should be ignored because it is not "up-to-date", (as opposed to Wilkinson and Pickett's own study, which was published in 2006).
This reveals the second biggest problem with Wilkinson and Pickett (next to their persistent academic dishonesty): their lack of understanding of stringent methodology. Deaton's conclusion that health and income distribution were not related was based on methodological weaknesses, and the inability to establish any causation between inequality and life expectancy.
One symptom of this problem is that the correlation between health and inequality that is sometimes found vanishes in more careful studies that control for background variables (and in any case, since not all background variables can be measured and controlled for, there is a need for experimental methods to convincingly link inequality and poor health).
Modern health economists simply have higher criteria than Wilkinson and Pickett, and require more than simple correlations. This is why the consensus view of the literature is the opposite as Wilkinson and Pickett.
This methodological problem has not been addressed in the few years that have passed between Deaton's study and Wilkinson and Pickett's study. There is simply not even one study that manages to causally link inequality to poor health, published before 2003 or between 2003 and now. The claim that Deaton's study is outdated is thus simply false.
But let us pretend for a moment that the Wilkinson and Pickett study is right and Deaton's wrong. It would have been the easiest thing in the world for the authors to refute Deaton. Instead, the strategy by Wilkinson and Pickett is to ignore the most heavyweight review study in academia in front of their non-academic public, that cannot be expected to know the state of the science. This is deeply dishonest tactics.
Regarding the most up-to-date research, we can further point to the paper "Inequality and mortality: Long-run evidence from a panel of countries" (A Leight and C Jencks, Journal of Health Economics, 2007) where it is noted that "the relationship between income inequality and health is either non-existent or too fragile to show up in a robustly estimated panel specification."
The studies by Deaton and Leight and Jencks have a full grasp of the dangers of confounding when using correlative evidence to assess causality. Thus to the extent that any consensus exists within Health Economics about the relationship between income distribution and life expectancy, it is that no such causal effect has as of yet been established. Yet Wilkinson and Pickett lend these important articles zero weight, neglecting to even cite them, despite their authoritative state in the literature.
It is interesting that Wilkinson and Pickett refer to a paper by Kondo et al. in their response, giving the impression that the research in question supports their extreme theories about how inequality is partially responsible for most, if not all, social ills. Contrary to Wilkinson and Pickett's insinuation, the Kondo et al. review never claims that they have causally linked inequality with poor health, instead consistently referring to an “association”. They further note that the findings need to be interpreted with
"caution given the heterogeneity between studies, as well as the attenuation of the risk estimates in analyses that attempted to control for the unmeasured characteristics of areas with high levels of income inequality."
(Income inequality, mortality, and self rated health: a meta-analysis of multilevel studies, British Medical Journal 2009)
In layman's terms, once background variables are controlled for, the link between inequality and health vanishes, exactly as found in the previous research. Wilkinson and Picket persistently confound causality and correlation.
Another interesting issue is that Wilkinson and Pickett refer to research by Robinson et al. (Inequality, race, and mortality in U.S. cities: a political and econometric review of Deaton and Lubotsky, Soc Sci Med 2009) when arguing that Deaton and Lubotsky are wrong in claiming that the relationship between mortality and income inequality vanishes once demographics are controlled for. However, they do not even mention the response to this article!
In the response from Deaton and Lubotsky we can read:
"Deaton and Lubotsky (2003) found that the robust positive relationship across American cities between mortality and income inequality became small, insignificant, and/or non-robust once they controlled for the fraction of each city's population that is black. Ash and Robinson (Ash, M., & Robinson D. Inequality, race, and mortality in US cities: a political and econometric review. Social Science and Medicine, 2009) consider alternative weighting schemes and show that in one of our specifications, in one data period, and with one of their alternative weighting schemes, income inequality is estimated to be a risk factor. All of our other specifications, as well as their own preferred specification, replicate our original result, which is supported by the weight of the evidence. Conditional on fraction black, there is no evidence for an effect of income inequality on mortality."
(Income inequality and mortality in U.S. cities: Weighing the evidence. A response to Ash, Soc Sci Med 2009)
Again, the strategy from Wilkinson and Pickett is very simple – only refer to the research that supports their own ideas, completely neglecting other works regardless of how important they are. Wilkinson and Pickett should be open about this approach, not pretending to represent a balanced perspective to the readers of The Spirit Level.
Those interested in the issue should note that already in 2002 professor of public health Johan Mackenbach wrote in a survey:
"Overall these papers reinforce the idea that the evidence for a correlation between income inequality and the health of the population is slowly dissipating. There is very little confirmation of such a relation outside the United States. Within the United States it has still to be convincingly demonstrated that it is not due to curvilinear individual level relationships and confounding."
(Income inequality and population health, British Medical Journal, 2002)
The general public - the target audience for “The Spirit Level” - cannot be expected to be aware of the state of research in the field. Wilkinson and Pickett exploit the trust of their readers and give them the impression that their claims represent consensus science, when the opposite is closer to the truth.
We also note that Wilkinson and Pickett write that “there are now over 200 studies testing [the relationship between inequality and life expectancy].” They give a similar response to another one of our questions, referring to their 2006 review noted above. But in the review they themselves write:
“We identified 168 analyses in 155 papers reporting research findings on the association between income distribution and population health”
(Income inequality and population health: a review and explanation of the evidence, Social Science & Medicine 2006)
How do 155 papers dealing with health magically change to over 200 papers dealing with life expectancy? Can Wilkinson and Pickett please explain this? Our guess is that they cannot.
Our Original Question
Q3. Correlation is not causation. This is true both for simple relationships and with multiple variables. Do you have any studies that actually establish a relationship between life expectancy and inequality, based on exogenous variation of inequality, quasi-experiments or any other well identified source of variation?
Response from Wilkinson and Pickett
Indeed, correlation is not necessarily proof of causation. However, as epidemiologists, we are trained in researching causal relationships within an observational framework. One of our critics has admitted that "sociology has been remarkably inept at providing us with the evidence and tools to create a better society". We agree, but epidemiology has been much more successful in uncovering causal influences on population health and in pointing the way to effective public health policy. Epidemiologists have been able, within an observational framework, to show that: smoking causes lung cancer; sleep position affects babies' risk of dying; social status and social networks have a profound impact of on people's risk of chronic disease, etc...
We discuss the epidemiological criteria for the establishment of causality in our book. One example might strike readers as a useful illustration. At the end of the Second World War, the USA was a very equal country, and ranked high on population health; Japan was a very unequal country and ranked very poorly on population health. Since then, these two countries have switched their relative positions: the USA is now very unequal and ranks very low on health; Japan became much more equal and its life expectancy increased faster than any other developed country till it had the highest life expectancy in the world. See also the study by Clarkwest et al referenced in point 4 below 18. There are a number of papers dealing with changes over time, with path analysis, and with causal ordering. In addition, a number of the associations found in observational studies of humans, including biological measurements, have been supported by genuine experiments on non-human primates where social status can be manipulated while material standards are kept constant.
Wilkinson and Pickett avoid answering our question. They only cite one article relating to China. (Provincial income inequality and self-reported health status in China during 1991-7, J Epidemiol Community Health 2006).
To begin with, we wonder how this study is relevant when it only has 6 citations according to Google Scholar whilst Deaton's paper – with almost 100 times that many citations – is not relevant according to Wilkinson and Pickett?
Also, why do Wilkinson and Pickett suddenly turn to China – when their analysis (not least in "The Spirit Level") is focused on OECD nations?
Wilkinson and Pickett do write that there "are a number of papers" which show a causal link. Why do they not refer to these papers? We repeat the question: Do you have any studies that actually establish a relationship between life expectancy and inequality, based on exogenous variation of inequality, quasi-experiments or any other well identified source of variation?
Please, send us the papers that you have which actually show that inequality causes health problems in the industrialized world, not only is correlated with them.
Wilkinson and Pickett rely on simple correlation studies. But, if we observed a correlation between headaches and taking aspirin, we would not conclude that aspirin causes headaches. Similarly, that income distribution is occasionally found to be correlated with various social ills should not come as a surprise.
It is, in fact, difficult to imagine a social problem that does not plausibly depress the income of the impacted group in some way, thereby increasing income inequality and giving rise to a spurious correlation. Repeating the flawed methodology on numerous occasions will not magically turn correlation into causation.
In modern social sciences, researchers tend to understand the need to conduct in-depth statistical analysis when dealing with complex economic phenomenon such as income inequality. Wilkinson and Pickett do not rely on statistical methods that actually separate between simple correlation and causality, even though the question they are engaging in is particularly prone to complex ties between variables.
Our Original Questions
4. Your most famous claim is that "inequality kills". Yet, using OECD life expectancy data, UN life expectancy data, OECD Gini and UN Gini, with different selections of countries, in several specifications, we again and again fail to replicate your result and find any statistically significant relationship between life expectancy and inequality. Is the explanation that you have relied on cherry picking – using the exact selection of measures, countries and year where such a correlation can be shown to exist?
5. Your initial defence for the lack of a statistically significant relationship between life expectancy and inequality from OECD data was that we should look at the working age population. Do you have any further defence, given that the OECD data shows no statistically significant relationship for the population between the ages of 15 and 60?
6. If inequality (rather than poverty) is strongly related to poor health, why can we not find any statistically significant relationship between inequality and health outcomes, as measured by the OECD for 16 of 19 health variables?
Response from Wilkinson and Pickett
The claim that ‘inequality kills’ has been made for us, in publishers’ publicity and in translation. However the weight of the evidence from studies of either infant or adult mortality, among both rich and poor countries, the American states, the regions of Russia, the provinces of China, the counties of Chile and many more suggests it does. Relationships between income inequality and life expectancy have been repeatedly demonstrated since 1979 13. There are over 200 tests of this link, internationally and in the US states, and the vast majority of studies confirm the adverse impact of inequality on health.
However, after periods in which income distribution has changed rapidly, the cross-sectional international association between income inequality and life expectancy have sometimes seemed to disappear 15 – only to reappear later 16. This seems to be because there are substantial lag periods between changes in income distribution and changes in population health. Every cause of death, and death rates in every age group have different lag periods. Death rates in later life are known to be powerfully influenced by experience in early life. Taking this into account it is surprising that relationships between health and inequality have been demonstrated so many times in so many different contexts. But we accept that the inequality/health relationship is one of the weaker associations demonstrated in The Spirit Level – no doubt partly for the reasons just described. Because lag periods are much shorter for infant mortality these relationships have been more consistent as have the association among US states. However, two new pieces of evidence leave little room for doubt as to the veracity of these relationships.
One is a study published in the British Medical Journal – a meta-analysis of multi-level studies of income inequality and health. This shows unequivocally that, even after controlling for individual income or education, inequality is related to significantly higher mortality rates. The second is a study showing that US states with bigger increases in inequality between 1970 and 2000 had less improvement in life expectancy than those with smaller increases.
After our criticism in, amongst others, the Wall Street Journal, Wilkinson and Pickett are suddenly backing away from the main claim in their book – that inequality kills. In fact, they did so already in a response in the same journal.
We are glad that Wilkinson and Pickett are admitting that the notion that "inequality kills" is misleading, but it is interesting to note that they put the responsibility on their publishers and the translators. Isn´t it the responsibility of the authors to control how their book is portrayed?
In fact, one can note that a previous book authored by Wilkinson was marketed with the same byline "Inequality Kills" (see the Guardian review of the book "The Impact of Inequality" in 2005. The title of the article was "Inequality Kills").
If Wilkinson and Pickett are in fact backing away from the claim "inequality kills", they should contact all journalists etc. who have referred to this as the main argument for their book, explaining that they do not support this claim. Have they explained this for all the audiences that they have spoken to? Or are they dishonestly marketing their book with an analysis they know to be false?
More importantly, Wilkinson and Pickett are deflecting. As we wrote in our fourth question
"Your most famous claim is that "inequality kills". Yet using OECD life expectancy data, UN life expectancy data, OECD Gini and UN Gini, with different selection of countries, in several specifications, we again and again fail to replicate your result and find any statistically significant relationship between life expectancy and inequality. Is the explanation that you have relied on cherry picking – using the exact selection of measures, countries and year where such a correlation can be shown to exist?"
Can Wilkinson and Pickett please explain why the relationship they show in their own book only appears if the exact 'right' definition of equality, the 'right' selection of countries and the 'right' year is chosen? This form of cherry-picking, or rather data-mining to use the correct term, is highly unscientific and dishonest to the readers. If Wilkinson and Pickett claim that The Spirit Level has any scientific validity left, they should give a detailed response to this question.
Again the "over 200" studies are referred to establishing a link between life expectancy and inequality – while this is in fact a reference to Wilkinson and Pickett's own research regarding the relationship between health and inequality, looking at 155 papers.
Wilkinson and Pickett do not, at all, respond to our fifth question. Is this simply because they have no answer to give? Are they willing to admit that they are wrong yet again? Why did they tell us to look at the working age population, when no correlation exists for this group either? Why give false and misleading answers if their book is based on research?
Perhaps most importantly, Wilkinson and Pickett do not respond to our sixth question either. Let us repeat the question: "If inequality (rather than poverty) is strongly related to poor health, why can we not find any statistically significant relationship between inequality and health outcomes as measured by the OECD for 16 of 19 health variables?"
If Wilkinson and Pickett cannot give a simple, straight-forward, answer to our sixth question, they should simply admit that The Spirit Level is based on data-mining and is not to be viewed as being based on objective science. The alternative is to explain why their 'correlations' fall apart as soon as they are compared with the OECD health parameters.
Our Original Question
Q7. If inequality is strongly related to life expectancy, why have the countries with the highest increase in inequality witnessed, on average, higher increases in life expectancy in the last two decades according to OECD data?
Response from Wilkinson and Pickett
Researching changes in inequality and changes in outcomes is difficult, and needs careful thought about lag times. The widening of income distribution which started in the late 1970s or early 1980s; followed the spread of neo-liberal economic and political thinking from the English speaking countries to other countries. While income differences rose rapidly in the 1980s in several English speaking countries, it remained stable in a number of other developed countries before spreading to them a decade or two later. The question is which period are current improvements in health related really to – current increases in inequality or the earlier stability? So you may have the relationships exactly the wrong way round. But if you have good evidence it should be presented in a peer reviewed journal. Clarkwest and colleagues 18 have shown that states with greater changes in inequality between 1970 and 2000 have had less improvement in life expectancy than those with smaller increases.
So when the correlation does not point in the direction that Wilkinson and Pickett would like it to be, suddenly they stop interpreting correlation with causation?
It is of course a very valid point that correlation should not be seen as causation. But given how Wilkinson and Pickett base all of their analysis on correlations (many of which disappear once we examine them, since they are the result of data-mining), we are puzzled by how Wilkinson and Pickett are thinking. Is the logic simply: We ignore everything that is not pointing in the way we like it to and exaggerate everything that does? Is this supposed to be scientific?
Wilkinson and Pickett refer to the paper “Neo-materialist theory and the temporal relationship between income inequality and longevity change” (Social Science & Medicine 2008). The paper has three citations according to Google Scholar, so we understand very well why Wilkinson and Pickett refer to it whilst they believe the work of Deaton (only 565 citations) to be unimportant.
More importantly, let us look at what is written in the abstract of the paper Wilkinson and Pickett refer to:“Contrary to findings from prior research, analyses also reveal a strong negative association between change in inequality and change in longevity once initial levels of inequality and other state characteristics are controlled."
So the paper supports the Wilkinson and Pickett theory, but in its own abstract notes that the findings go against other research. The paper is on an entirely different scientific level than Wilkinson and Pickett's work, since it is honest in acknowledging research that points in another direction. Not surprisingly, Wilkinson and Pickett only refer to this paper, not to those that support the opposite viewpoint.
Our Original Question
Q8. Why do you claim that more unequal nations have less creativity, (and that Portugal is as creative as the United States), when data from the World Intellectual Patent Organization shows the opposite?
Response from Wilkinson and Pickett
We used data from the World Intellectual Patent Organisation. This shows patents per capita for Portugal at 0.6 and the USA at 1.0. In contrast, patents per capita for Japan are 7.8 and for Sweden 30.1.
This is almost sad. Wilkinson and Pickett have not used the World Intellectual Patent Organisation as a source, but instead refer to amateur internet site - Nationmaster - as a basis for their 'scientific' claims.
Let us look at the actual data from the World Intellectual Patent Organisation. There we can read that between 1995 and 2007, the number of patent fillings per million inhabitants in Portugal rose from 8.08 to 14.98. In the US, the corresponding figures are 465.54 and 702.50 for the same years.
So the latest data – from the actual World Intellectual Patent Organisation – shows there were almost 50 times as many patents in the US as in Portugal. Wilkinson and Pickett believe that the two nations have as many patents, since they rely on embarrassingly incorrect data.
Here is how Wilkinson and Pickett can look up the data from the actual source:
1. Go to the site http://www.wipo.int/ipstats/en/statistics/patents/
2. Click on the link "Resident patent filings per million population (1995-2007)" and look at the data.
Are Wilkinson and Pickett going to deflect yet again, refer to hundreds of studies, claim that their editors are to blame? Or will they admit that they are very wrong?
A researcher who 'finds' that the US has only as few patents per capita as Portugal should of course realise that she or he is using a flawed data source. A researcher should also actually use the data source she or he is referring to (the World Intellectual Patent Organization in this case) and not just a site on the web. Wilkinson and Pickett instead become exited over their 'findings', using it as a main argument for their thesis in The Spirit Level. This clearly shows how unscientific the book is. We would be delighted to see if Wilkinson and Pickett can explain their 'research' to us.
Our Original Question
Q9. Why do you claim that more unequal nations have more mental illnesses (and that the United Kingdom has 250% the mental illness level of Germany) when data from the World Health Organisation shows the opposite?
Response from Wilkinson and Pickett
We use W.H.O. data designed to provide comparable estimates of the prevalence of mental illness. Rather than reflecting the use of medical and psychiatric services as the data on which this question is based does, the data we used is based on the scientific collection of data using standardised diagnostic interviews administered to random samples of the population. The question reflects a confusion epidemiologists are taught to avoid at the beginning of their training. The only reason W.H.O. went to the expense of collecting the data we used is that help-seeking behaviour is a very unreliable guide to the prevalence of health problems.
Clearly, Wilkinson and Pickett have noted that the actual data from the W.H.O. database over mental illness does not correlate with inequality in the way that they would like. They do not explain this to their readers, instead choosing data from a much smaller sample of nine countries that does support their ideas.
This if far from scientific, far from being honest to the readers.
Our Original Question
Q10. Why do you claim that "[i]n Sweden, people don't bother to check your tickets on the train or bus" when this is obviously not the case? The American audience reading the Boston Globe might believe you, but anybody who has lived in or visited Sweden will immediately see through the deception.
Response from Wilkinson and Pickett
We have, happily, visited both Sweden and the USA several times recently so our claims are based on our own experiences in those countries. But our experiences are borne out by the evidence on trust.
All three authors of this response live in Sweden and have done so for the better parts of their lives. We have used Swedish trains, buses and metros for transportation thousands of times. When you go on a Swedish bus, you show your ticket or buy one. Occasionally, several inspectors board the bus and check that nobody has somehow cheated (by for example buying a ticket to stop A but instead travelling further to stop B).
When you travel with a Swedish train, your ticket will be checked. In the Stockholm metro system, significant investments have been made to stop people from jumping over the barriers without paying for a ticket. And, yet again, random checks are performed on the metro.
There is no chance that a person who actually has visited several times would be unaware of this, as the metal barriers are clearly visible. We are confident that in this case Wilkinson and Pickett are not simply misleading the readers of the Boston Globe; but rather lying to them, safe in the knowledge that few Americans are aware of how Swedish public transport works.
Are Wilkinson and Pickett willing to say anything – no matter how false – to "prove" their point? Is this because modern research, which separates causality from correlation, has shown their theories about inequality to be untrue?