Authors: Sasha Issenberg
In 1943, a New Jersey chemist isolated streptomycin, an antibiotic that put up a promising fight against tuberculosis, and the pharmaceutical manufacturer Merck began producing it in large volumes. After the war ended, several companies in the United Kingdom, where the disease killed twenty-five thousand residents annually, made plans to introduce their own streptomycin. Meanwhile, a Mayo Clinic tuberculosis researcher traveled to London and Oxford to trumpet findings from his successful
laboratory experiments on guinea pigs. The Medical Research Council received fifty kilograms of streptomycin and was quickly overwhelmed by requests from tuberculosis patients for some of the miracle cure. For Hill, who had become honorary director of the council’s statistical research unit, the medicine shortage offered a promising opportunity to try a new type of experiment.
There was only a distant precedent for the idea of randomly splitting patients into separate groups and measuring the varying effects of treatments on each. The seventeenth-century Flemish physician and chemist Jan Baptista van Helmont had defended his technique by daring academic rivals to “take out of the hospitals, out of the camps, or from elsewhere, 200 or 500 poor People that have Fevers, Pleurisies, etc. Let us divide them into halfes, let us cast lots, that one half of them may fall to my share, and the other to yours … we shall see how many funerals both of us shall have.” Into the twentieth century, however, such controlled testing came to be seen as ethically dodgy, since it meant consciously denying the best known care to those who wanted it. But because there wasn’t enough streptomycin for everyone who requested it, the council had no choice but to leave people untreated. A decision to pass over some people randomly, Hill realized, offered an opportunity to improve the statistical quality of an important clinical experiment—and would also be a fairer method of distributing potentially lifesaving medicine.
Hill set out to translate Fisher’s technique from the farm to the hospital. Each of the 107 tuberculosis patients in Hill’s study was randomly assigned a number that put him in one of two treatment groups.
The “S” cases were to receive two grams of streptomycin daily, spread over four doses, along with bed rest. The “C” cases were assigned only bed rest. Even once admitted to the hospital, a patient never learned which treatment he or she had been assigned.
After one year, Hill’s investigators reviewed the health of the whole sample: a majority of the patients assigned streptomycin, 56 percent, had improved their condition over the course of their hospitalization, compared
with 31 percent of the control sample. Over the same period, 22 percent of the S cases had died, compared with 46 percent of the C cases. Since Hill had randomized the treatment, there was only one way to explain the result: the new medicine worked. British companies began manufacturing streptomycin, which became an essential tool in the doctor’s bags of those fighting tuberculosis, since most of the others were scalpels to cut a hole in the patient’s chest and an air pump to collapse the infected lungs.
In an era in which wonder drugs emerged from labs worldwide, such blind randomized-control experiments quickly became the dominant tool for demonstrating that a new treatment worked and delivered no mitigating side effects.
When, a few years later, Jonas Salk isolated a vaccine for polio, a successful large-scale randomized experiment—involving 1.8 million children—was a natural way to test it.
In 1962, the Food and Drug Administration changed its standards to require “adequate and
well-controlled investigations,” and not merely clinical judgment, before approving a drug for wide use.
Gerber and Green believed they could bring this approach into politics. They wanted to explain electoral behavior with the same degree of authority that doctors now had in describing therapeutic care. Instead of patients, they would randomize individual households to separate the factors that affected voter participation. Most of the money in major campaigns was spent on television and radio, and it was impossible to treat one voter differently from a neighbor when broadcast waves covered a whole region. But individualized forms of contact—a canvasser’s knock on the door, a pamphlet arriving in the mail, live or recorded phone calls—could be easily isolated.
Gerber was three years younger than Green, a political scientist by curiosity more than training. Gerber had arrived at Yale from MIT, where he earned a graduate degree in economics just as the school was becoming known as a center for cutting-edge research employing novel tools to examine subjects outside the typical bounds of economic study. Gerber and a classmate, Steve Levitt, kept being drawn to political questions, like
whether the winner’s fund-raising advantage could explain the outcome of congressional elections. (Levitt later won a John Clark Bates Medal and cowrote the bestselling book
Freakonomics
, exploring subjects such as the hierarchy of drug gangs and the ethics of sumo wrestlers.)
In his dissertation, Gerber used economic techniques to answer the type of question usually left to political scientists or historians: what happened when the United States adopted the secret ballot in the 1880s? That moment, when Americans went from picking their candidates aloud in crowded pubs to making their selections in curtained solitude, was key in forming the country’s modern political culture, but it had never been analyzed in that way. “Until you read about the adoption of the secret ballot it would never occur to you that the secret ballot would need to be adopted,” says Gerber. He wanted to know whether the shift had had an impact on how many Americans turned out on election day, how incentives might have changed when voting was converted from a public act to a private one. “At the most general level it seems pretty obvious that the payoffs for voting are social and psychological, not instrumental,” says Gerber. “It seems very hard to imagine people figuring out the idea of the payoff for voting being literally your odds of being the pivotal vote.”
The world of elections was not an academic abstraction to Gerber, who had spent just enough time around political campaigns to be interested when Green suggested putting their methods to the test. The stories that stuck with him from his own campaign experiences were ones that revealed a deep crisis of knowledge among those who practiced politics for a living. In 1987, not long after graduating from Yale, a twenty-three-year-old Gerber went to work as the New Hampshire scheduling director on Paul Simon’s presidential campaign, responsible for managing the Illinois senator’s itinerary in the first primary state. One day, he fielded a call from Simon’s top Illinois-based consultant, a former journalist named David Axelrod, who was working on a batch of radio ads attacking one of Simon’s midwestern rivals, Missouri congressman Dick Gephardt. “He even supported the neutron bomb,” one of Axelrod’s scripts read.
“For reasons not entirely clear to me, he asked the scheduler,” recalls Gerber, referring to himself, “ ‘How do you think that’ll play in New Hampshire?’ ”
“I’m not sure people in New Hampshire will know what the neutron bomb is,” Gerber told Axelrod.
After he started teaching at Yale in 1993, Gerber interned for a summer in the Washington office of Democratic pollster Mark Mellman to get a different perspective on the way campaigns worked. One of the firm’s polls itemized a list of qualities and asked voters if they would be more likely to support a candidate who shared that trait—including, to Gerber’s amusement, “doesn’t listen too much to polls.”
Just as Green was coming to question his discipline, some political scientists had begun to conclude that the whole political-consulting profession was a farce. With nearly a half century of rich electoral data and ever-better measurements of national conditions, researchers had thought that they could explain presidential outcomes with a basic set of facts—primarily which party held power and how the economy fared while they did. Ads, debates, candidate speeches, and election organizing were mere spectacle at the margins of a predetermined outcome. The debate was summarized by an unusually succinct question:
Do campaigns matter?
The more time Gerber spent within Mellman’s polling operation, the more he appreciated that political scientists themselves lacked the tools to ever arrive at a convincing answer. Much of what academics thought they knew came from exit polls and post-election surveys like the University of Michigan’s national election studies. Pollsters would ask people whether or not they voted, if they were contacted by a campaign before the election, then look for a correlation between the two. Gerber saw flaws in this method. He assumed that the people who answered polls were more likely to be those reachable by campaigns. Logic suggested also that respondents highly attuned to politics were more likely than others to remember when they were contacted by campaigns. Campaigns decide which voters to contact in the first place based on their own calculations of who is more
likely to vote. “If you put this all together, you get a causal explanation of who knows what?” says Gerber. “These are technical issues, but until they are resolved you have no good answer to the question you are trying to understand.”
SHORTLY BEFORE ELECTION DAY
in 1998, Don Green and Alan Gerber walked through the streets of New Haven trying to monitor the dozens of students they had dispatched across the city, keeping an eye on approaching rain clouds and fretting that when they arrived there wouldn’t be enough umbrellas to keep everyone dry. They had recruited off Yale bulletin boards, promising the generous pay of twenty dollars per hour, and assigned students into pairs according to buddy-system precepts. Where possible, Gerber and Green tried to hire local residents to serve as Sherpas in unfamiliar city neighborhoods. They checked in with their employees often and called everybody back in from the field at dusk. “We tried not to take chances,” says Green. The students were knocking on doors to encourage people to vote in an upcoming election; that Green referred to this as “dangerous work” was evidence of just how detached, and sheltered, political science had grown from the world it supposedly studied.
Gerber and Green had designed a field experiment to measure what effects, if any, the most fundamental campaign methods could have on an election’s outcome.
They had selected three basic modes of voter contact—an oversized postcard arriving by mail, a scripted ring from a far-off call center employee, and a doorstep visit from a canvasser—and within each a series of different appeals to participate on November 3. One message pointed to an idea of civic duty, with an image of Iwo Jima, under the slogan “They fought … so we could have something to vote for.” Another raised themes of community solidarity: “When people from our neighborhood don’t vote we give politicians the right to ignore us.” The last emphasized the prospect of a close election, illustrated with a “Dewey Defeats
Truman” headline. “Will yours be the deciding vote?” the postcard version asked. Various combinations of mode, message, and number of contacts were randomly deployed across thirty thousand New Haven voters scattered among twenty-nine of the city’s thirty wards. (To “get away from students,” as they later put it, the Yale professors removed the ward including the university from their study.) A control group would go without any contact. Afterward Gerber and Green would check the electoral rolls maintained by the town clerk to measure the influence of each type of contact on voter turnout.
Despite the national furor over the looming impeachment of Bill Clinton, there was little suspense about the outcomes of the top statewide races in Connecticut that fall. The state’s popular Republican governor, John Rowland, and its longtime Democratic senator, Chris Dodd, were both going to be comfortably reelected. But the experiment made no reference to the particulars of that year’s ballot, largely because Gerber and Green had chosen to partner with nonprofit groups prohibited by the tax code from taking a side in elections. That summer the two professors had presented their plan—which amounted, in essence, to creating their own political action committee for the sake of the experiment—to the local League of Women Voters chapter, which agreed to attach its name to the project. Then Gerber and Green found a Connecticut foundation willing to put up nearly fifty thousand dollars for the operation in the hopes that it would yield new strategies for increasing civic engagement after a generation of falling participation nationwide.
In that regard, the timing of Gerber and Green’s gambit was fortuitous; everybody wanted to understand why Americans seemed to be retreating from public life. Three years earlier, Harvard professor Robert Putnam had emerged as the most visible political scientist in the country on the basis of a journal article titled “Bowling Alone: America’s Declining Social Capital.” (It would later become the basis for a bestselling book.)
Putnam looked at declining membership figures in nonpolitical community organizations—from bowling leagues to Elks Lodges and the League
of Women Voters, whose ranks had shrunk nearly in half nationwide since the late 1960s—to argue that a distinctively American civil society had dissolved into a fizz of solitary entertainments and self-interest. Putnam mostly kept clear of electoral politics in his article, but the same pattern was apparent there, too: between 1960 and 1988, voter turnout rates in presidential campaign years fell by 12 percentage points. A director of the University of Michigan’s National Election Studies at the time, Steven Rosenstone, dove into decades’ worth of survey data in search of explanation. In a 1993 book resulting from that effort, Rosenstone and John Mark Hansen had spread responsibility widely. The electorate had expanded (with the constitutional change of the voting age to eighteen) while individual voters grew disengaged (they were less attached to candidates and parties, and had lost confidence in their electoral power). But much of the blame, according to Rosenstone and Hansen, belonged to politicians themselves for losing touch with voters as they embraced new media.
Party organizations that had once mobilized votes by speaking directly with their constituents had receded into the background, replaced by candidate campaigns that chose to blare their messages over the airwaves.