Overall, the United States incarcerated 2,166,260 persons at yearend 2002… 1 in every 143 U.S. residents were incarcerated in State or Federal prison or a local jail. There were 5.9 million adults in the ‘correctional population’ by the end of 1998. This means that 2.9% of the U.S. adult population — 1 in every 34 — was incarcerated, on probation or on parole. The Bureau of Justice Statistics reports that in 1999, the nation spent $146,556,000,000 on the Federal, State and Local justice systems. Based on this information the cost per inmate year was: Corrections, judicial, legal and police costs: $78,154 per inmate per year. The average sentence in 2000 for federal convicts was almost 5 years; for non-violent crimes, 6 years.
Prisoners sentenced for drug offenses constituted the largest group of Federal inmates (55%) in 2001… In 2001, drug law violators comprised 20.4% of all adults serving time in State prisons. Over 80% of the increase in the federal prison population from 1985 to 1995 was due to drug convictions. The U.S. nonviolent prisoner population is larger than the combined populations of Wyoming and Alaska.
The United States has the highest prison population rate in the world, some 686 per 100,000 of the national population, followed by the Cayman Islands (664), Russia (638), Belarus (554), Kazakhstan (522), Turkmenistan (489), Belize (459), Bahamas (447), Suriname (437) and Dominica (420). More than 8.75 million people are held in penal institutions throughout the world, mostly as pre-trial detainees (remand prisoners) or having been convicted and sentenced. About half of these are in the United States (1.96m), Russia (0.92m) or China.
Department of corrections data show that about a fourth of those initially imprisoned for nonviolent crimes are sentenced for a second time for committing a violent offense. Whatever else it reflects, this pattern highlights the possibility that prison serves to transmit violent habits and values rather than to reduce them. If one compares 1996 to 1984, the crime index is 13 points higher. This dramatic increase occurred during an era of mandatory minimum sentencing and “three strikes you’re out.”
States spent $32.5 billion on Corrections in 1997 alone. To compare, states only spent $22.2 billion on cash assistance to the poor. California state government expenditures on prisons increased 30% from 1987 to 1995, while spending on higher education decreased by 18%.
Prior to 1972, the number of prisoners had grown at a steady rate that closely tracked growth rates in the general population. Between 1925 (the first year national prison statistics were officially collected) and 1972, the number of state prisoners increased from 85,239 to 174,379. Starting in 1973, however, the prison population and imprisonment rates began to rise precipitously. This change was fueled by stiffer sentencing and release laws and decisions by courts and parole boards, which sent more offenders to prison and kept them there for longer terms.
This study… will argue that orthodox competition and monopoly theory is inherently flawed and misleading and cannot rationally support any antitrust policy. Further, it will demonstrate that the business organizations under indictment in the classic antitrust cases were expanding outputs, reducing prices, improving technology, and engaging generally in an intensely competitive process. It will conclude that both antitrust theory and history are an elaborate mythology with no solid foundation in either logic or fact.
Many volumes on the subject have presented a welter of antitrust cases, void of relevant conduct and performance information. Consequently, any serious consideration of the indicted firms’ actual behavior have been conspicuously absent. Apparently, these volumes expect readers to assume that the firms indicted under the antitrust statutes were actually raising prices, reducing outputs, producing shoddy products, colluding successfully with competitors, driving competitors from the market with predatory practices, and generally abusing consumers in the marketplace.
The industries accused of “monopolization” by Senator Sherman and his colleagues in 1890 were expanding production four times more rapidly than the economy as a whole for the decade prior to the Sherman Act (some as much as ten times faster) and were dropping their prices even faster than the general price level was falling during that deflationary period.
The trusts “have made products cheaper, have reduced prices,” admitted Congressman William Mason, who nevertheless was in favor of an anti-trust law. He was in favor of the law because he, and most of his congressional colleagues, wanted to protect less-efficient businesses in their districts from competition. Antitrust has always been a protectionist racket.
Standard Oil caused the price of refined petroleum to fall from over 30 cents per gallon in 1869 to 5.9 cents by 1897 while stimulating an enormous amount of innovation in the industry… For this great service to consumers, Rockefeller was prosecuted and forced to break up his company.
In his masterpiece, Antitrust and Monopoly: Anatomy of a Policy Failure, Dominick Armentano carefully examined fifty-five of the most famous antitrust cases in U.S. history and concluded that in every single case, the accused firms were dropping prices, expanding production, innovating, and generally benefiting consumers. It was their less-efficient competitors who were “harmed,” as they should have been.
For example, the American Tobacco Company was found guilty of “monopolization” in 1911, even though the price of cigarettes (per thousand) had declined from $2.77 in 1895 to $2.20 in 1907, despite a 40 percent increase in raw material costs.
In 1962 the government forbade the Brown Shoe Company, which had 1 percent of the shoe market, from acquiring Kinney Shoes, which also had a 1 percent market share. A company with 2 percent of the shoe market, according to the government, constituted a monopoly.
In 1962 the government forced the Schwinn Bicycle Company to divorce itself from its network of dealers; foreign competition eventually drove Schwinn into bankruptcy.
General Motors was never prosecuted, but because of the company’s fear of antitrust it was official company policy from 1937 until 1956 to never let its market share top 45 percent, for any reason. This fear of antitrust prosecution contributed to the industry’s dramatic losses in market share to the Japanese and German automakers during the 1970s and ’80s.
RCA was prohibited by antitrust regulators from charging royalties to American licensees, so the company licensed its products to Japanese companies. The entire Japanese electronics industry is based on this.
Antitrust regulation killed Pan American World Airways by forbidding it from acquiring domestic routes. Lacking “feeder” traffic for its international flights, the company went bankrupt.
The recent era of antitrust reassessment has resulted in general agreement among economists that the most successful instances of cartelization and monopoly pricing have involved companies that enjoy the protection of government regulation of prices and government control of entry by new competitors. Occupational licensing and trucking regulation, for example, have allowed competitors to alter terms of competition and legally prevent entry into the market. Unfortunately, monopolies created by the federal government are almost always exempt from antitrust laws, and those created by state governments frequently are exempt as well. Municipal monopolies (e.g., taxicabs, utilities) may be subject to antitrust action but often are protected by statute.
One of the most worrisome statistics in antitrust is that for every case brought by government, private plaintiffs bring ten. The majority of cases are filed to hinder, not help, competition. According to Steven Salop, formerly an antitrust official in the Carter administration, and Lawrence J. White, an economist at New York University, most private antitrust actions are filed by members of one of two groups. The most numerous private actions are brought by parties who are in a vertical arrangement with the defendant (e.g., dealers or franchisees) and who therefore are unlikely to have suffered from any truly anticompetitive offense. Usually, such cases are attempts to convert simple contract disputes (compensable by ordinary damages) into triple-damage payoffs under the Clayton Act.
The second most frequent private case is that brought by competitors. Because competitors are hurt only when a rival is acting procompetitively by increasing its sales and decreasing its price, the desire to hobble the defendant’s efficient practices must motivate at least some antitrust suits by competitors. Thus, case statistics suggest that the anticompetitive costs from “abuse of antitrust,” as New York University economists William Baumol and Janusz Ordover (1985) referred to it, may actually exceed any procompetitive benefits of antitrust laws.
I was amazed when I started researching antitrust that no economist had ever actually looked into the notion that trusts of the late 19th century were actually restricting or expanding output. I couldn’t find any book… I looked at hundreds of sources and I couldn’t find any data at all. It was just an assumption that was thrown out there. So when you read things like this, always look for the evidence. And if there’s none, you should be suspicious of that and look for it yourself. (47:36)
American industry as a whole was intensely competitive in the period from 1875 on. Many industries, including the railroads, had overexpanded and were facing a squeeze on profits. American history contains the myth that the railroads faced practically no competition at all during this period, that freight rates constantly rose, pinching every last penny out of the shippers, especially the farmers, and bleeding them to death. Historian Kolko shows that:
Contrary to the common view, railroad freight rates, taken as a whole, declined almost contiuously over the period [from 1877 to 1916] and although consolidation of railroads proceeded apace, this phenomenon never affected the long-term decline of rates or the ultimately competitive nature of much of the industry. In their desire to establish stability and control over rates and competition, the railroads often resorted to voluntary, cooperative efforts.
The two major means used by competitors to cut into each other’s markets were rate wars (price cutting) and rebates; the aim of business leaders was to stop these. Their major, unsuccessful, tool was the “pool” which was continuously broken up by competitive factors.4 The first serious pooling effort in the East, sponsored by the New York Central, had been tried as early as 1874 by Vanderbilt; the pool lasted for six months. In September 1876,a Southwestern Railroad Association was formed by seven major companies in an attempt to voluntarily enforce a pool; it didn’t work and collapsed in early 1878. Soon it became obvious to most industrial leaders that the pooling system was ineffective.
In 1876 the first significant federal regulatory bill was introduced into the House by J. R. Hopkins of Pittsburgh. Drawn up by the attorney for the Philadelphia and Reading Railroad, it died in committee.
By 1879, there was “a general unanimity among pool executives … that without government sanctions, the railroads would never maintain or stabilize rates.”5 By 1880, the railroads were in serious trouble; the main threat was identified as “cutthroat competition.”
Far from pushing the economy toward greater centralization, economic forces indicated that centralization was inefficient and unstable. The push was towards decentralization, and smaller railroads often found themselves much less threatened by economic turns of events than the older, more established and larger business concerns.
Thus the Marxist model finds itself seriously in jeopardy in this instance, for the smaller forms and railroads, throughout the crises of the 1870s and 1880s often were found to be making larger profits on capital invested than the giant businesses. Furthermore, much of the concentration of economic power which was apparent during the 1870s and on, was the result of massive state aid immediately before, during, and after the Civil War, not the result of free market forces. Much of the capital accumulation – particularly in the cases of the railroads and banks – was accomplished by means of government regulation and aid, not by free trade on a free market.
Also, the liberal and conservative models which stress the supposed fact that there was growing centralization in the economy and that competition either lessened or became less intense, are both shaken by historical facts. And we already have seen that it was the railroad leaders, faced with seemingly insurmountable problems, who initiated the drive for federal government regulation of their industry.
Rate wars during 1881 pushed freight rates down 50 percent between July and October alone; between 1882 and 1886, freight rates declined for the nation as a whole by 20 percent. Railroads were increasingly talking about regulation with a certain spark of interest. Chauncey Depew, attorney for the New York Central, had become convinced “of the [regulatory commission’s] necessity … for the protection of both the public and the railroads.6 He soon converted William H. Vanderbilt to his position.7
Agitation for regulation to ease competitive pains increased, and in 1887, the Interstate Commerce Act was passed. According to the Railway Review, an organ of the railroad, it was only a first step.
The Act was not enough, and it did not stop either the rate wars or rebates. So, early in 1889 during a prolonged rate war, J. P. Morgan summoned presidents of major railroads to New York to find ways to maintain rates and enforce the act, but this, too, was a failure. The larger railroads were harmed most by this competition; the smaller railroads were in many cases more prosperous than in the early 1880s. “Morgan weakened rather than strengthened many of his roads … [and on them] services and safety often declined. Many of Morgan’s lines were overexpanded into areas where competition was already too great.”8 Competition again increased. The larger roads then led the fight for further regulation, seeking more power for the Interstate Commerce Commission (ICC).
In 1891, the president of a midwestern railroad advocated that the entire matter of setting rates be turned over to the ICC. An ICC poll taken in 1892 of fifteen railroads showed that fourteen of them favored legalized pooling under Commission control.
Another important businessman, A. A. Walker, who zipped back and forth betwene business and govenrment agencies, said that “railroad men had had enough of competition. The phrase ‘free competition’ sounds well enough as a universal regulator,” he said, “but it regulates by the knife.”9
In 1906, the Hepburn Act was passed, also with business backing. The railroad magnate Cassatt spoke out as a major proponent of the act and said that he had long endorsed federal rate regulation. Andrew Carnegie, too, popped up to endorse the act. George W. Perkins, an important Morgan associate, wrote his boss that the act “is going to work out for the ultimate and great good of the railroad.” But such controls were not enough for some big businessmen. Thus E. P. Ripley, the president of the Santa Fe, suggested what amounted to a Federal Reserve System for the railroads, cheerfully declaring that such a system “would do away with the enormous wastes of the competitive system, and permit business to follow the line of least resistance” – a chant later taken up by Mussolini.
In any case, we have seen that (a) the trend was not towards centralization at the close of the nineteenth century – rather, the liquidation of previous malinvestment fostered by state action and bank-led inflation worked against the bigger businesses in favor of the smaller, less overextended businesses; (b) there was, in the case of the railroads anyway, no sharp dichotomy or antagonism between big businessmen and the progressive Movement’s thrust for regulation; and (c) the purpose of the regulations, as seen by key business leaders, was not to fight the growth of “monopoly” and centralization, but to foster it.
The culmination of this big-business-sponsored “reform” of the economic system is actually today’s system. The new system took effect immediately during world War I when railroads gleefully handed over control to the government in exchange for guaranteed rate increases and guaranteed profits, something continued under the Transportation Act of 1920. The consequences, of course, are still making themselves felt, as in 1971, when the Pennsylvania Railroad, having cut itself off from the market and from market calculation nearly entirely, was found to be in a state of economic chaos. It declared bankruptcy and later was rescued, in part, by the state…
Mergers often were tried, as in the railroad industry, but the larger mergers brought neither greater profits nor less competition. As Kolko states: “Quite the opposite occurred. There was more competition, and profits, if anything, declined.” A survey of ten mergers showed, for instance, that the companies earned an average of 65 percent of their preconsolidation profits after consolidation. Overcentralization inhibited their flexibility of action, and hence their ability to respond to changing market conditions. In short, things were not as bad for other industries as for the railroads – they were often worse.
Regarding historical evidence, if the thesis of the critics of capitalism were true, then one would have to expect a more pronounced tendency toward monopolization under relatively freer, unhampered, unregulated laissez-faire capitalism than under a relatively more heavily regulated system of “welfare” or “social” capitalism. However, history provides evidence of precisely the opposite result. There is general agreement regarding the assessment of the historical period from 1867 to World War I as being a relatively more capitalist period in history of the United States, and of the subsequent period being one of comparatively more and increasing business regulations and welfare legislation.
However, if one looks into the matter one finds that there was not only less development toward monopolization and concentration of business taking place in the first period than in the second but also that during the first period a constant trend towards more severe competition with continually falling prices for almost all goods could be observed. And this tendency was only brought to a halt and reversed when in the course of time the market system became more and more obstructed and destroyed by state intervention. Increasing monopolization only set in when leading businessmen became more successful at persuading the government to interfere with this fierce system of competition and pass regulatory legislation, imposing a system of “orderly” competition to protect existing large firms from the so-called cutthroat competition continually springing up around them.
The computing system named Watson, will compete on Jeopardy! against the show’s two most successful and celebrated contestants — Ken Jennings and Brad Rutter — on February 14, 15 and 16.
The grand prize for this competition will be $1 million, with second place earning $300,000, and third place earning $200,000. Rutter and Jennings will donate 50 percent of their winnings to charity, and IBM will donate 100 percent of its winnings to charity.
Watson’s ability to understand the meaning and context of human language, and rapidly process information to find precise answers to complex questions, holds enormous potential to transform how computers help people accomplish tasks in business and their personal lives. Watson will enable people to rapidly find specific answers to complex questions. The technology could be applied in areas such as healthcare, for accurately diagnosing patients, to improve online self-service help desks, to provide tourists and citizens with specific information regarding cities, prompt customer support via phone, and much more.
Despite “recklessly” increasing its numbers during the past millennium, humanity has never been better fed, healthier, or longer lived. The state of humanity has never been better.
Since Malthus wrote his Essay on Population two centuries ago, the average person’s life span has more than doubled. He is better educated and wealthier. She is freer to choose her rulers and express her views. He is more likely to live under the rule of law and is less fearful of being arbitrarily deprived of life, limb, freedom, property, wealth, and other basic human rights. Her professional, social, and physical mobility, while still limited in many places, is less likely to be circumscribed by caste, class, location, or other accidents of birth. Not only is work less physically demanding, he works fewer hours, earns more, and has more leisure time at his disposal.
The proximate causes for the improvements in the human condition… are the forces of technological change and economic growth, supplemented by trade in products, ideas, and technologies associated with those forces.
Virtually every indicator of human welfare also improves with wealth, as do the environmental indicators that we know to have the greatest bearing on public health… In the United States, this upward march has been in progress at least since the 1880s… Pollution levels did not keep pace with the growth in population or consumption of energy, other natural resources, and chemicals… Despite a 100-fold increase in organic chemical usage, public health has continued to improve… The inverse trends between chemical usage and public health is consistent with the notion that new technology does not, in fact, make matters worse. If anything, it replaces worse risks with risks that are not so bad… In fact, the air and water quality in the United States and the world’s rich nations are better today than they have been in decades. The increase in their agricultural productivity has allowed them to reestablish forests and set habitat aside… As the cases of the Clean Air Act of 1970, Clean Water Act of 1972, and Safe Drinking Water Act of 1974 show, much of the improvements in the United States for the air and water quality indicators examined in chapter 6 preceded the enactment of stringent national environmental laws.
Although many of today’s developing countries haven’t been on the cycle of progress for long, Human Development Indices in their urban areas exceed those in rural areas. This might seem counterfactual to many casual observers given the obvious- and very visible- squalor and pollution in the cities of developing countries such as Mexico City; Teheran, Iran; and New Delhi, India… Because rural areas are generally poorer, they lack access to many of the technologies that have improved human well-being in urban areas… The case of sanitary reform in India also hints at the importance of economic growth… Sanitary reform came to India in 1870, well before it was introduced in Italy in 1890… However, even now, large portions of the Indian population lack access to sanitation. Clearly, neither technology transfer nor knowledge of a technology’s potential is sufficient to stimulate technological change.
I have mentioned good humor as one of the preservatives of our peace and tranquility. It is among the most effectual, and its effect is so well imitated and aided, artificially, by politeness, that this also becomes an acquisition of first rate value. In truth, politeness is artificial good humor, it covers the natural want of it, and ends by rendering habitual a substitute nearly equivalent to the real virtue. It is the practice of sacrificing to those whom we meet in society, all the little conveniences and preferences which will gratify them, and deprive us of nothing worth a moment’s consideration; it is the giving a pleasing and flattering turn to our expressions, which will conciliate others, and make them pleased with us as well as themselves. How cheap a price for the good will of another! When this is in return for a rude thing said by another, it brings him to his senses, it mortifies and corrects him in the most salutary way, and places him at the feet of your good nature, in the eyes of the company. But in stating prudential rules for our government in society, I must not omit the important one of never entering into dispute or argument with another. I never saw an instance of one of two disputants convincing the other by argument. I have seen many, on their getting warm, becoming rude, and shooting one another. Conviction is the effect of our own dispassionate reasoning, either in solitude, or weighing within ourselves, dispassionately, what we hear from others, standing uncommitted in argument ourselves. It was one of the rules which, above all others, made Doctor Franklin the most amiable of men in society, “never to contradict anybody.” If he was urged to announce an opinion, he did it rather by asking questions, as if for information, or by suggesting doubts. When I hear another express an opinion which is not mine, I say to myself, he has a right to his opinion, as I to mine; why should I question it? His error does me no injury, and shall I become a Don Quixote, to bring all men by force of argument to one opinion? If a fact be misstated, it is probable he is gratified by a belief of it, and I have no right to deprive him of the gratification. If he wants information, he will ask it, and then I will give it in measured terms; but if he still believes his own story, and shows a desire to dispute the fact with me, I hear him and say nothing. It is his affair, not mine, if he prefers error.
The sign of rationality is nothing else but the capability of both entities… to engage in discussion. If that is not possible, then we have no ethical problem, then we only have technical problems. Now, given all of the ethical problems that arise out of having conflicts with other entities, if they can be solved at all, must be solved in the form of argumentation — talking back and forth — and, if the fact that talking back and forth, a proponent talking with an opponent, since this arguing does not just consist of free flowing sounds, but requires the use of our physical body (vocal cords, brains, and so forth), in any discussion that we engage in, we implicitly admit the ownership, the property, of each person in his personal body… If I would not recognize the ownership of my opponent and his body, there would be no reason for me to ever talk to him, and likewise the opponent… If we were silent then nobody can ask for any justification of anything. As soon as we begin to talk to each other, then implicitly we must admit our mutual recognition of property in our own bodies. That is also what makes it possible for us to agree on the fact that we have disagreed.
Unlike physics or biology, the social sciences have not demonstrated the capacity to produce a substantial body of useful, nonobvious, and reliable predictive rules about what they study—that is, human social behavior, including the impact of proposed government programs.
The missing ingredient is controlled experimentation, which is what allows science positively to settle certain kinds of debates. How do we know that our physical theories concerning the wing are true? In the end, not because of equations on blackboards or compelling speeches by famous physicists but because airplanes stay up. Social scientists may make claims as fascinating and counterintuitive as the proposition that a heavy piece of machinery can fly, but these claims are frequently untested by experiment, which means that debates like the one in 2009 will never be settled. For decades to come, we will continue to be lectured by what are, in effect, Keynesian and non-Keynesian economists.
Over many decades, social science has groped toward the goal of applying the experimental method to evaluate its theories for social improvement. Recent developments have made this much more practical, and the experimental revolution is finally reaching social science. The most fundamental lesson that emerges from such experimentation to date is that our scientific ignorance of the human condition remains profound. Despite confidently asserted empirical analysis, persuasive rhetoric, and claims to expertise, very few social-program interventions can be shown in controlled experiments to create real improvement in outcomes of interest.
James Lind is conventionally credited with executing the first clinical trial in the modern sense of the term. In 1747, he divided 12 scurvy-stricken crew members on the British ship Salisbury into six treatment groups of two sailors each. He treated each group with a different therapy, tried to hold all other potential causes of change to their condition as constant as possible, and observed that the two patients treated with citrus juice showed by far the greatest improvement.
But clinical trials place an enormous burden on being sure that the treatment under evaluation is the only difference between the two groups. And as experiments began to move from fields like classical physics to fields like therapeutic biology, the number and complexity of potential causes of the outcome of interest—what I term “causal density”—rose substantially. It became difficult even to identify, never mind actually hold constant, all these causes.
In 1884, the brilliant but erratic American polymath C. S. Peirce hit upon a solution when he randomly assigned participants to the test and control groups. Random assignment permits a medical experimentalist to conclude reliably that differences in outcome are caused by differences in treatment. That’s because even causal differences among individuals of which the experimentalist is unaware—say, that genetic predisposition—should be roughly equally distributed between the test and control groups, and therefore not bias the result.
In theory, social scientists, too, can use that approach to evaluate proposed government programs. In the social sciences, such experiments are normally termed “randomized field trials” (RFTs).
By about a quarter-century ago, however, it had become obvious to sophisticated experimentalists that the idea that we could settle a given policy debate with a sufficiently robust experiment was naive. The reason had to do with generalization, which is the Achilles’ heel of any experiment, whether randomized or not.
A detailed review of every regression model published between 1968 and 2005 in Criminology, a leading peer-reviewed journal, demonstrated that these models consistently failed to explain 80 to 90 percent of the variation in crime. Even worse, regression models built in the last few years are no better than models built 30 years ago.
But sophisticated experimentalists understood that because of the issue’s high causal density, there would be hidden conditionals to the simple rule that “mandatory-arrest policies will reduce domestic violence.” The only way to unearth these conditionals was to conduct replications of the original experiment under a variety of conditions. Indeed, Sherman’s own analysis of the Minnesota study called for such replications. So researchers replicated the RFT six times in cities across the country. In three of those studies, the test groups exposed to the mandatory-arrest policy again experienced a lower rate of rearrest than the control groups did. But in the other three, the test groups had a higher rearrest rate.
From those 122 criminology experiments, I extracted the 103 that were conducted in the United States and grouped them into 40 “program concepts”: mandatory arrest for domestic violence, intensive probation, and so on. Of these 40 concepts, 22 had more than one trial. Of those 22, only one worked each time it was tested: nuisance abatement, in which the owners of blighted properties were encouraged to clean them up. And even nuisance abatement underwent only two trials.
So what do we know, based on this series of experiments, about reducing crime? First, that most promising ideas have not been shown to work reliably. Second, that nuisance abatement—which is at the core of what is often called “Broken Windows” policing—tentatively appears to work. Even that conclusion needs qualification: it’s a safe bet that there is some jurisdiction in the United States where even Broken Windows would fail. We must remain open to the iconoclast who will find the limits of our conclusions—just as the hard sciences always devote some resources to those who try to unseat conventional wisdom. That is, experimentation does not create absolute knowledge but rather changes both the burden and the standard of proof for those who disagree with its findings.
What businesses have figured out is that they can deal with the problem of causal density by scaling up the testing process. Run enough tests, and you can find predictive rules that are sufficiently nuanced to be of practical use in the very complex environment of real-world human decision making. This approach places great emphasis on executing many fast, cheap tests in rapid succession, rather than big, onetime “moon shots.” It’s something like the replacement of craft work by mass production. The crucial step was to lower the cost and time of each test, which doesn’t simply make the process more efficient but, by allowing many more test iterations, leads to faster and more useful learning.
First, few programs can be shown to work in properly randomized and replicated trials. Despite complex and impressive-sounding empirical arguments by advocates and analysts, we should be very skeptical of claims for the effectiveness of new, counterintuitive programs and policies, and we should be reluctant to trump the trial-and-error process of social evolution in matters of economics or social policy.
Second, within this universe of programs that are far more likely to fail than succeed, programs that try to change people are even more likely to fail than those that try to change incentives.
And third, there is no magic. Those rare programs that do work usually lead to improvements that are quite modest, compared with the size of the problems they are meant to address or the dreams of advocates.
It is tempting to argue that we are at the beginning of an experimental revolution in social science that will ultimately lead to unimaginable discoveries. But we should be skeptical of that argument. The experimental revolution is like a huge wave that has lost power as it has moved through topics of increasing complexity. Physics was entirely transformed. Therapeutic biology had higher causal density, but it could often rely on the assumption of uniform biological response to generalize findings reliably from randomized trials. The even higher causal densities in social sciences make generalization from even properly randomized experiments hazardous. It would likely require the reduction of social science to biology to accomplish a true revolution in our understanding of human society—and that remains, as yet, beyond the grasp of science.
At the moment, it is certain that we do not have anything remotely approaching a scientific understanding of human society. And the methods of experimental social science are not close to providing one within the foreseeable future. Science may someday allow us to predict human behavior comprehensively and reliably. Until then, we need to keep stumbling forward with trial-and-error learning as best we can.
In 2001, Michael Jennions, a biologist at the Australian National University, set out to analyze “temporal trends” across a wide range of subjects in ecology and evolutionary biology. He looked at hundreds of papers and forty-four meta-analyses (that is, statistical syntheses of related studies), and discovered a consistent decline effect over time, as many of the theories seemed to fade into irrelevance. In fact, even when numerous variables were controlled for—Jennions knew, for instance, that the same author might publish several critical papers, which could distort his analysis—there was still a significant decrease in the validity of the hypothesis, often within a year of publication… Jennions argues that the decline effect is largely a product of publication bias, or the tendency of scientists and scientific journals to prefer positive data over null results, which is what happens when no effect is found. The bias was first identified by the statistician Theodore Sterling, in 1959, after he noticed that ninety-seven per cent of all published psychological studies with statistically significant data found the effect they were looking for. A “significant” result is defined as any data point that would be produced by chance less than five per cent of the time. This ubiquitous test was invented in 1922 by the English mathematician Ronald Fisher, who picked five per cent as the boundary line, somewhat arbitrarily, because it made pencil and slide-rule calculations easier. Sterling saw that if ninety-seven per cent of psychology studies were proving their hypotheses, either psychologists were extraordinarily lucky or they published only the outcomes of successful experiments. In recent years, publication bias has mostly been seen as a problem for clinical trials, since pharmaceutical companies are less interested in publishing results that aren’t favorable. But it’s becoming increasingly clear that publication bias also produces major distortions in fields without large corporate incentives, such as psychology and ecology.
In the late nineteen-nineties, John Crabbe, a neuroscientist at the Oregon Health and Science University, conducted an experiment that showed how unknowable chance events can skew tests of replicability… The disturbing implication of the Crabbe study is that a lot of extraordinary scientific data are nothing but noise. The hyperactivity of those coked-up Edmonton mice wasn’t an interesting new fact—it was a meaningless outlier, a by-product of invisible variables we don’t understand. The problem, of course, is that such dramatic findings are also the most likely to get published in prestigious journals, since the data are both statistically significant and entirely unexpected. Grants get written, follow-up studies are conducted. The end result is a scientific accident that can take years to unravel.
Such anomalies demonstrate the slipperiness of empiricism. Although many scientific ideas generate conflicting results and suffer from falling effect sizes, they continue to get cited in the textbooks and drive standard medical practice. Why? Because these ideas seem true. Because they make sense. Because we can’t bear to let them go. And this is why the decline effect is so troubling. Not because it reveals the human fallibility of science, in which data are tweaked and beliefs shape perceptions. (Such shortcomings aren’t surprising, at least for scientists.) And not because it reveals that many of our most exciting theories are fleeting fads and will soon be rejected. (That idea has been around since Thomas Kuhn.) The decline effect is troubling because it reminds us how difficult it is to prove anything. We like to pretend that our experiments define the truth for us. But that’s often not the case. Just because an idea is true doesn’t mean it can be proved. And just because an idea can be proved doesn’t mean it’s true. When the experiments are done, we still have to choose what to believe.
[Schooler] notes that nobody even tries to replicate most science papers—there are simply too many. (According to Nature, a third of all studies never even get cited, let alone repeated.) “I’ve learned the hard way to be exceedingly careful,” Schooler says. “Every researcher should have to spell out, in advance, how many subjects they’re going to use, and what exactly they’re testing, and what constitutes a sufficient level of proof. We have the tools to be much more transparent about our experiments.”
One of the classic examples of selective reporting concerns the testing of acupuncture in different countries. While acupuncture is widely accepted as a medical treatment in various Asian countries, its use is much more contested in the West. These cultural differences have profoundly influenced the results of clinical trials. Between 1966 and 1995, there were forty-seven studies of acupuncture in China, Taiwan, and Japan, and every single trial concluded that acupuncture was an effective treatment. During the same period, there were ninety-four clinical trials of acupuncture in the United States, Sweden, and the U.K., and only fifty-six per cent of these studies found any therapeutic benefits. As Palmer notes, this wide discrepancy suggests that scientists find ways to confirm their preferred hypothesis, disregarding what they don’t want to see. Our beliefs are a form of blindness.
If any human acts may loosely be called causeless, they are the minor acts of a healthy man; whistling as he walks; slashing the grass with a stick; kicking his heels or rubbing his hands. It is the happy man who does the useless things; the sick man is not strong enough to be idle. It is exactly such careless and causeless actions that the madman could never understand; for the madman (like the determinist) generally sees too much cause in everything. The madman would read a conspiratorial significance into those empty activities. He would think that the lopping of the grass was an attack on private property. He would think that the kicking of the heels was a signal to an accomplice. If the madman could for an instant become careless, he would become sane. Every one who has had the misfortune to talk with people in the heart or on the edge of mental disorder, knows that their most sinister quality is a horrible clarity of detail; a connecting of one thing with another in a map more elaborate than a maze. If you argue with a madman, it is extremely probable that you will get the worst of it; for in many ways his mind moves all the quicker for not being delayed by the things that go with good judgment. He is not hampered by a sense of humour or by charity, or by the dumb certainties of experience. He is the more logical for losing certain sane affections. Indeed, the common phrase for insanity is in this respect a misleading one. The madman is not the man who has lost his reason. The madman is the man who has lost everything except his reason.
Nevertheless, he is wrong. But if we attempt to trace his error in exact terms, we shall not find it quite so easy as we had supposed. Perhaps the nearest we can get to expressing it is to say this: that his mind moves in a perfect but narrow circle. A small circle is quite as infinite as a large circle; but, though it is quite as infinite, it is not so large. In the same way the insane explanation is quite as complete as the sane one, but it is not so large…
In these cases it is not enough that the unhappy man should desire truth; he must desire health. Nothing can save him but a blind hunger for normality, like that of a beast. A man cannot think himself out of mental evil; for it is actually the organ of thought that has become diseased, ungovernable, and, as it were, independent.
