But there is also evidence that scientific fraud is on the increase. A number of sensational cases came to light in 2015, and the incidence of retracted, withdrawn, and corrected scientific papers has increased steadily over the past decade. Indeed, some pharmaceutical companies have decided to no longer rely on the results of published studies, fearing that many of these are not trustworthy. Some have argued that the growing scientific misconduct reflects the use of new technologies for uncovering it—such as programs that check for plagiarism. Technological advances have certainly played a role, but in my opinion this doesn’t entirely explain the deluge of failures to replicate.
A more compelling explanation is the fiercely competitive nature of science, which has accelerated in recent years. Grants are much harder to get funded, so that even applications ranked by peer review as “very good” are no longer above the pay line. So faculty at research universities must spend the bulk of their time writing grant proposals, with the probability of funding often being less than 10 percent. At the same time, the most highly ranked scientific journals have increased their rejection rates considerably; acceptance rates in the neighborhood of 5 percent are not uncommon. Moreover, the editors of the top journals (based on the recommendations of anonymous referees) often request additional experiments, which requires considerably more time, expense, and effort with no guarantee that the final product will be accepted for publication. For practitioners of science the level of stress has never been greater. Is it any wonder that some succumb to a shortcut method to success by “fudging” their results to get a competitive edge?
I’m not suggesting that simply increasing the amount of available funding for research would abate this problem. The solution will require a multifaceted approach. One step that should be seriously considered is a substantial increase in the penalty for scientific fraud, with jail time for those who have wasted precious research dollars. Today, those who are caught often get away relatively unscathed, in some instances receiving a substantial buyout package to leave their place of employment, because of the nature of the university tenure system. This trend must be reversed to ensure the viability of the scientific enterprise.
Sub-Prime Science
Nicholas Humphrey
Emeritus Professor of Psychology, London School of Economics; Visiting Professor of Philosophy, New College of the Humanities; Senior Member, Darwin College, Cambridge; author, Soul Dust
In August 2015, Brian Nosek and the Open Science Collaboration published a report in Science on the replicability of findings previously published in top-rank psychology journals: “We conducted replications of 100 experimental and correlational studies . . . using high-powered designs and original materials when available.” Only 36 percent of the replications were successful. Among the findings that didn’t replicate were these:
“People are more likely to cheat after they read a passage informing them that their actions are determined and thus that they don’t have free will.”
“People make less severe moral judgments when they’ve just washed their hands.”
“Partnered women are more attracted to single men when they’re ovulating.”
These particular findings may not be game-changing. But they have been widely cited by other researchers (including me).
In many cases there may well be innocent explanations for why the original study gave the unreliable results it did. But in more than a few cases it can only be put down to slipshod research, too great haste to publish, or outright fraud. Worryingly, the more newsworthy the original finding, the more likely it could not be replicated. Insiders have likened the situation to a trainwreck.
John Brockman likes to quote Stewart Brand: “Science is the only news. When you scan through a newspaper or magazine, all the human interest stuff is the same old he-said-she-said, . . . a pathetic illusion of newness. . . . Human nature doesn’t change much; science does.” But we have here a timely reminder that the distinction between science and journalism is not—and has never been—as clear-cut as Brand imagines.
The reality is that science itself has always been affected by “the human interest stuff.” Personal vendettas, political and religious biases, stubborn adherence to pet ideas have in the past led even some of the greatest scientists to massage experimental data and skew theoretical interpretations. Happily, the body of scientific knowledge has continued to live and grow despite such human aberrations. In general, scientists continue to play by the rules.
But we must not be complacent. The professional culture is changing. In many fields, and not of course only in psychology, science is becoming more of a career path than a noble vocation, more of a feeding trough than a chapel of truth. Sub-prime journals are flourishing. Bonuses are growing. After the disgrace of the bankers, science must not be next.
The Infancy of Meta-Science
Jonathan Schooler
Professor, Department of Psychological and Brain Sciences, UC Santa Barbara
A defining feature of science is its ability to evolve in response to new developments. Historically, changes in technological capacities, quantitative procedures, and scientific understanding have all contributed to large-scale revisions in the conduct of scientific investigations. Pressure is mounting for further improvements. In disciplines such as medicine, psychology, genetics, and biology, researchers have been confronting findings that are not as robust as they initially appeared. Such shrinking effects raise questions not only about the specific findings they challenge but more generally, about the confidence we can have in published results that have yet to be re-evaluated.
In attempting to understand its own limitations, science is fueling the consolidation of an emerging new discipline: meta-science. Meta-science, the science of science, attempts to use quantifiable scientific methodologies to show how current scientific practices influence the truth of scientific conclusions. This endeavor is joining the agendas of a variety of fields, including medicine, biology, and psychology—each seeking to understand why some initial findings fail to fully replicate. Meta-science has its roots in the philosophy of science and the study of scientific methods but is distinguished from the former by its reliance on quantitative analysis and from the latter by its broad focus on the general factors contributing to the limitations and successes of scientific investigations.
An ambitious meta-scientific study was recently published in Science by Brian Nosek and the Open Science Collaboration. A large-scale effort in psychology sought to replicate 100 “quasi-randomly” selected studies from three premier journals and found that less than half reached traditional levels of significance when replicated. This study is noteworthy because it directed the lens of science not at any particular phenomenon but rather at the process of science itself. In this sense, it represents one of the first major implementations of evidence-based meta-science.
Although I’m enthusiastic about the meta-scientific goals this study exemplifies, I worry that major limitations in its design and implementation may have produced a misleadingly pessimistic assessment of the health of the field of psychology. Numerous factors may have contributed to an underestimation of the reliability of the findings, including variations in the skills and motivations of the replicating scientists, limitations in the statistical power of the replications, and perhaps most important, questions regarding the fidelity with which the original methods were reproduced. Although the authors attempted to vet their replication procedure with the originating lab, many of the replicated studies were conducted without the originating lab’s endorsement, and these unapproved efforts disproportionately contributed to the low replication estimate.
Even the studies that used procedures approved by the originating laboratories may have been lacking in fidelity. For example, one of the more well-known findings that failed to replicate involved the observation that exposing people to an anti–free-will message can increase cheating. I’m particularly familiar with this example (and perhaps biased to defend i
t), as I was a co-author of the original study. Although we signed off on the replication protocol, we subsequently discovered a small but important detail that was left out of the replicating procedure. In the original study, but not the replication, the anti–free-will message was framed as part of an entirely different study. We have recently found that people are less likely to change their beliefs about free will when the anti–free-will message is introduced as part of the same study. Apparently people are reluctant to change their mind on this important topic if they feel coerced to do so. In this context, it is notable that in the replication study, the anti–free-will message failed to significantly discourage participants from believing in free will in the first place, and thus could hardly have been expected to produce the further ramification of increased cheating. I suspect that a big portion of failures to replicate may involve the omission of similar small but important methodological details.
As the emerging field of meta-science moves forward, it will be important to refine techniques for understanding how disparities between original studies and replications may contribute to difficulties in reproducing results. Increasing the transparency of originally conducted studies, through methods such as detailed pre-registration, is likely to make it easier for replication teams to understand precisely how the project was originally implemented. However, it will also be important to develop methods for evaluating the fidelity of the reproductions themselves.
Another important next step for meta-science is the implementation of prospective replication experiments that systematically investigate how new hypotheses fare when tested repeatedly across laboratories. Prospective replication experiments will help to overcome potential biases inherent in selecting which published studies to replicate, while simultaneously illuminating various factors that may govern the replicability of scientific findings, including variations in population sample, researcher investment, and reproduction fidelity.
As we adopt a more meta-scientific perspective, researchers will increasingly appreciate that just as a single study cannot irrefutably demonstrate the existence of a phenomenon, neither can a single failure to replicate disprove it. Over time, scientists will likely become more comfortable with meticulously documenting and (ideally) pre-registering all aspects of their research. They will see the replication of their work not as a threat to their integrity but as testament to their work’s importance. They will recognize that replicating other findings is an important component of their scientific responsibilities. They will refine replication procedures not only to discern the robustness of findings but also to understand their boundary conditions and the reasons they sometimes (often?) decline in magnitude. Even if history shows that the original foray into meta-science was significantly lacking, ultimately meta-science will surely offer deep insights into the nature of the scientific method itself.
The Disillusion and the Disaffection of Poor White Americans
Richard Nisbett
Theodore M. Newcomb Distinguished Professor of social psychology; codirector, Culture and Cognition program, University of Michigan at Ann Arbor; author, Mindware
The mortality rate for whites 45 to 54 years old with no more than a high school education increased by 134 deaths per 100,000 people from 1999 to 2014.
—New York Times, Nov. 2, 2015
Over the past fifteen years or so, the mortality rate for poorly educated middle-aged whites living in the U.S. South and West increased significantly. Mortality did not increase for middle-aged blacks, Hispanics, or any other ethnic group, nor for whites in other regions of the country, nor for poorly educated whites in other rich countries. The death rates that are most elevated are those for suicide, cirrhosis of the liver, heroin overdose, and other causes suggesting self-destructive behavior.
There is some controversy about just how great the increase in mortality is, and whether it holds only for women or for both men and women, but there is no debate about the fact that late-middle-aged poor American whites are doing relatively badly with respect to mortality rates—both as compared with other Americans and as compared with people in rich countries generally. And the warning signs that something is very wrong with white people at the bottom of the American economic ladder are mounting rapidly.
The worsening plight of poor white Americans highlighted by the Times article on the mortality findings by Princeton economists Angus Deaton and Anne Case is by no means limited to just the South and West. Researchers from political science to neuroscience have been uncovering ever more disturbing facts about whites at the bottom of the U.S. socioeconomic ladder. Charles Murray, in his book Coming Apart (2012), showed that between 1960 and 2010 the bottom 30 percent of Americans in terms of socioeconomic status (SES) experienced a collapse in social capital. The rate of children from broken marriages and living with a single parent increased tenfold over that period—to 25 percent. The rate of children living with both biological parents when the mother was forty years old plummeted from 95 percent to 30 percent. The fraction of people having no involvement in any secular or religious organization more than doubled—to 34 percent. The percentage of prime-working-age males not in the workforce increased threefold, to 12 percent. The percentage of men not making enough to support a household of two more than doubled, to 30 percent. The percentage of males in state and federal prisons grew almost fivefold.
Murray examined the same variables for the 20 percent of the white population with the highest socioeconomic status. For none of these variables was there a notable worsening over the fifty-year period.
Sociologist Sean Reardon examined the gap between the academic achievement of the top 10 percent of the SES spectrum and the bottom 10 percent between the late 1940s and the early 2010s. He also examined the black/white gap in academic achievement over that time span. At the beginning of the period, the black/white gap was double the SES gap. At the end of that period, the SES gap was double the black/white gap. This crossover was due roughly in equal proportion to the gains of black children and the losses of lower-SES children.
Murray’s claim that the welfare state is responsible for the lassitude and misery of the American lower class would appear to be ruled out by the fact that the social safety net is much stronger in Europe, and nothing there is close to the dire straits of those at the bottom of American society. It’s easier to argue that it’s the lack of a European-style safety net that has contributed to the American debacle.
So, what is responsible for the malaise at the bottom? Scientists have contributed little but speculation to this question. But a case could be made that one cause is that faith in the American dream, while still alive at the top of the economic pyramid, is disappearing at the bottom, and that this is true for primarily economic reasons. When I moved to Ann Arbor decades ago, a high-school educated worker on the line at Ford made enough money to support a family of four, own a three-bedroom home in the suburbs, have two cars and a boat, and buy a cottage in Northern Michigan. That’s a higher standard of living for the poorly educated than was true in Europe then or now—or in the U. S. today. The poorly educated man today can expect to be an assistant manager of a chain store, a security guard, or a jack of all trades—occupations that barely support a single individual in modest fashion, let alone a family of four in comfort.
The disillusionment hypothesis explains why the support for Donald Trump’s candidacy is greatest among ill-educated whites in the poorer, less cosmopolitan regions of the country. Trump’s bombast, braggadocio, xenophobia, aggressiveness, and willingness to tell baldface lies is unnerving to anyone having a nodding acquaintance with the circumstances of the rise of fascism. Both Italian fascism and German Nazism achieved their greatest initial successes with the proletariat. In the case of Nazism, the greatest early gains were made among rural Protestant peasants.
Scientists have yet to develop convincing theories about what might alleviate the plight of poor whites at the bottom of the social ladder. Meanwhile we can only hope that t
he economic doldrums don’t worsen, producing receptivity higher up the economic ladder to demagogues.
Inequality of Wealth and Income: A Runaway Process
S. Abbas Raza
Founding Editor, 3QuarksDaily.com
One of the biggest challenges facing us is the increasing disparity in wealth and income which has become obvious in American society in the last four decades or so, with all its pernicious effects on societal health. Thomas Piketty’s data-backed tour de force, Capital in the Twenty-First Century (2013), gave us two alarming pieces of news about this trend: (1) Inequality is worse than we thought, and (2) it will continue to worsen because of structural reasons inherent in our form of capitalism, unless we do something.
The top 0.1 percent of families in America went from having 7 percent of national wealth in the late 1970s to having about 25 percent now. Over the same period, the income share of the top 1 percent of families has gone from less than 10 percent to more than 20 percent. And lest we think that even if wealth and income are more concentrated America is still the land of opportunity and those born with very little have a good chance to move up in economic class, a depressing number of studies show that according to standard measures of intergenerational mobility, the United States ranks among the least economically mobile of the developed nations.
Piketty shows that an internal feature of capitalism increases inequality: As long as the rate of return on capital (r) is greater than the rate of economic growth (g), wealth will tend to concentrate in a minority, and that the inequality r >
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