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Sociology and You
Quiz by Ricci Herr
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âThereâs No Such Thing as Sound Scienceâ by By Christie Aschwanden was a lead science writer for FiveThirtyEight. FiveThirtyEight, Science, Dec. 6, 2017 Science is being turned against itself. For decades, its twin ideals of transparency and rigor have been weaponized by those who disagree with results produced by the scientific method. Under the Trump administration, that fight has ramped up again. In a move ostensibly meant to reduce conflicts of interest, Environmental Protection Agency Administrator Scott Pruitt has removed a number of scientists from advisory panels and replaced some of them with representatives from industries that the agency regulates. Like many in the Trump administration, Pruitt has also cast doubt on the reliability of climate science. For instance, in an interview with CNBC, Pruitt said that âmeasuring with precision human activity on the climate is something very challenging to do.â Similarly, Trumpâs pick to head NASA, an agency that oversees a large portion the nationâs climate research, has insisted that research into human influence on climate lacks certainty, and he falsely claimed that âglobal temperatures stopped rising 10 years ago.â Kathleen Hartnett White, Trumpâs nominee to head the White House Council on Environmental Quality, said in a Senate hearing last month that she thinks we âneed to have more precise explanations of the human role and the natural roleâ in climate change. The same entreaties crop up again and again: We need to root out conflicts. We need more precise evidence. What makes these arguments so powerful is that they sound quite similar to the points raised by proponents of a very different call for change thatâs coming from within science. This other movement strives to produce more robust, reproducible findings. Despite having dissimilar goals, the two forces espouse principles that look surprisingly alike: Science needs to be transparent. Results and methods should be openly shared so that outside researchers can independently reproduce and validate them. The methods used to collect and analyze data should be rigorous and clear, and conclusions must be supported by evidence. These are the arguments underlying an âopen scienceâ reform movement that was created, in part, as a response to a âreproducibility crisisâ that has struck some fields of science.1 But theyâre also used as talking points by politicians who are working to make it more difficult for the EPA and other federal agencies to use science in their regulatory decision-making, under the guise of basing policy on âsound science.â Scienceâs virtues are being wielded against it. What distinguishes the two calls for transparency is intent: Whereas the âopen scienceâ movement aims to make science more reliable, reproducible and robust, proponents of âsound scienceâ have historically worked to amplify uncertainty, create doubt and undermine scientific discoveries that threaten their interests. âOur criticisms are founded in a confidence in science,â said Steven Goodman, co-director of the Meta-Research Innovation Center at Stanford and a proponent of open science. âThatâs a fundamental difference â weâre critiquing science to make it better. Others are critiquing it to devalue the approach itself.â Calls to base public policy on âsound scienceâ seem unassailable if you donât know the termâs history. The phrase was adopted by the tobacco industry in the 1990s to counteract mounting evidence linking secondhand smoke to cancer. A 1992 Environmental Protection Agency report identified secondhand smoke as a human carcinogen, and Philip Morris responded by launching an initiative to promote what it called âsound science.â In an internal memo, Philip Morris vice president of corporate affairs Ellen Merlo wrote that the program was designed to âdiscredit the EPA report,â âprevent states and cities, as well as businesses from passing smoking bansâ and âproactivelyâ pass legislation to help their cause. The sound science tactic exploits a fundamental feature of the scientific process: Science does not produce absolute certainty. Contrary to how itâs sometimes represented to the public, science is not a magic wand that turns everything it touches to truth. Instead, itâs a process of uncertainty reduction, much like a game of 20 Questions. Any given study can rarely answer more than one question at a time, and each study usually raises a bunch of new questions in the process of answering old ones. âScience is a process rather than an answer,â said psychologist Alison Ledgerwood of the University of California, Davis. Every answer is provisional and subject to change in the face of new evidence. Itâs not entirely correct to say that âthis study proves this fact,â Ledgerwood said. âWe should be talking instead about how science increases or decreases our confidence in something.â The tobacco industryâs brilliant tactic was to turn this baked-in uncertainty against the scientific enterprise itself. While insisting that they merely wanted to ensure that public policy was based on sound science, tobacco companies defined the term in a way that ensured that no science could ever be sound enough. The only sound science was certain science, which is an impossible standard to achieve. âDoubt is our product,â wrote one employee of the Brown & Williamson tobacco company in a 1969 internal memo. The note went on to say that doubt âis the best means of competing with the âbody of factââ and âestablishing a controversy.â These strategies for undermining inconvenient science were so effective that theyâve served as a sort of playbook for industry interests ever since, said Stanford University science historian Robert Proctor. The sound science push is no longer just Philip Morris sowing doubt about the links between cigarettes and cancer. Itâs also a 1998 action plan by the American Petroleum Institute, Chevron and Exxon Mobil to âinstall uncertaintyâ about the link between greenhouse gas emissions and climate change. Itâs industry-funded groupsâ late-1990s effort to question the science the EPA was using to set fine-particle-pollution air-quality standards that the industry didnât want. And then there was the more recent effort by Dow Chemical to insist on more scientific certainty before banning a pesticide that the EPAâs scientists had deemed risky to children. Now comes a move by the Trump administrationâs EPA to repeal a 2015 rule on wetlands protection by disregarding particular studies. (To name just a few examples.) Doubt merchants arenât pushing for knowledge, theyâre practicing what Proctor has dubbed âagnogenesisâ â the intentional manufacture of ignorance. This ignorance isnât simply the absence of knowing something; itâs a lack of comprehension deliberately created by agents who donât want you to know, Proctor said.2 In the hands of doubt-makers, transparency becomes a rhetorical move. âItâs really difficult as a scientist or policy maker to make a stand against transparency and openness, because well, who would be against it?â said Karen Levy, researcher on information science at Cornell University. But at the same time, âyou can couch everything in the language of transparency and it becomes a powerful weapon.â For instance, when the EPA was preparing to set new limits on particulate pollution in the 1990s, industry groups pushed back against the research and demanded access to primary data (including records that researchers had promised participants would remain confidential) and a reanalysis of the evidence. Their calls succeeded and a new analysis was performed. The reanalysis essentially confirmed the original conclusions, but the process of conducting it delayed the implementation of regulations and cost researchers time and money. Delay is a time-tested strategy. âGridlock is the greatest friend a global warming skeptic has,â said Marc Morano, a prominent critic of global warming research and the executive director of ClimateDepot.com, in the documentary âMerchants of Doubtâ (based on the book by the same name). Moranoâs site is a project of the Committee for a Constructive Tomorrow, which has received funding from the oil and gas industry. âWeâre the negative force. Weâre just trying to stop stuff.â Some of these ploys are getting a fresh boost from Congress. The Data Quality Act (also known as the Information Quality Act) was reportedly written by an industry lobbyist and quietly passed as part of an appropriations bill in 2000. The rule mandates that federal agencies ensure the âquality, objectivity, utility, and integrity of informationâ that they disseminate, though it does little to define what these terms mean. The law also provides a mechanism for citizens and groups to challenge information that they deem inaccurate, including science that they disagree with. âIt was passed in this very quiet way with no explicit debate about it â that should tell you a lot about the real goals,â Levy said. But whatâs most telling about the Data Quality Act is how itâs been used, Levy said. A 2004 Washington Post analysis found that in the 20 months following its implementation, the act was repeatedly used by industry groups to push back against proposed regulations and bog down the decision-making process. Instead of deploying transparency as a fundamental principle that applies to all science, these interests have used transparency as a weapon to attack very particular findings that they would like to eradicate. Now Congress is considering another way to legislate how science is used. The Honest Act, a bill sponsored by Rep. Lamar Smith of Texas,3 is another example of what Levy calls a âTrojan horseâ law that uses the language of transparency as a cover to achieve other political goals. Smithâs legislation would severely limit the kind of evidence the EPA could use for decision-making. Only studies whose raw data and computer codes were publicly available would be allowed for consideration. That might sound perfectly reasonable, and in many cases it is, Goodman said. But sometimes there are good reasons why researchers canât conform to these rules, like when the data contains confidential or sensitive medical information.4 Critics, which include more than a dozen scientific organizations, argue that, in practice, the rules would prevent many studies from being considered in EPA reviews.5 It might seem like an easy task to sort good science from bad, but in reality itâs not so simple. âThereâs a misplaced idea that we can definitively distinguish the good from the not-good science, but itâs all a matter of degree,â said Brian Nosek, executive director of the Center for Open Science. âThere is no perfect study.â Requiring regulators to wait until they have (nonexistent) perfect evidence is essentially âa way of saying, âWe donât want to use evidence for our decision-making,ââ Nosek said. Most scientific controversies arenât about science at all, and once the sides are drawn, more data is unlikely to bring opponents into agreement. Michael Carolan, who researches the sociology of technology and scientific knowledge at Colorado State University, wrote in a 2008 paper about why objective knowledge is not enough to resolve environmental controversies. âWhile these controversies may appear on the surface to rest on disputed questions of fact, beneath often reside differing positions of value; values that can give shape to differing understandings of what âthe factsâ are.â Whatâs needed in these cases isnât more or better science, but mechanisms to bring those hidden values to the forefront of the discussion so that they can be debated transparently. âAs long as we continue down this unabashedly naive road about what science is, and what it is capable of doing, we will continue to fail to reach any sort of meaningful consensus on these matters,â Carolan writes. The dispute over tobacco was never about the science of cigarettesâ link to cancer. It was about whether companies have the right to sell dangerous products and, if so, what obligations they have to the consumers who purchased them. Similarly, the debate over climate change isnât about whether our planet is heating, but about how much responsibility each country and person bears for stopping it. While researching her book âMerchants of Doubt,â science historian Naomi Oreskes found that some of the same people who were defending the tobacco industry as scientific experts were also receiving industry money to deny the role of human activity in global warming. What these issues had in common, she realized, was that they all involved the need for government action. âNone of this is about the science. All of this is a political debate about the role of government,â she said in the documentary. These controversies are really about values, not scientific facts, and acknowledging that would allow us to have more truthful and productive debates. What would that look like in practice? Instead of cherry-picking evidence to support a particular view (and insisting that the science points to a desired action), the various sides could lay out the values they are using to assess the evidence. For instance, in Europe, many decisions are guided by the precautionary principle â a system that values caution in the face of uncertainty and says that when the risks are unclear, it should be up to industries to show that their products and processes are not harmful, rather than requiring the government to prove that they are harmful before they can be regulated. By contrast, U.S. agencies tend to wait for strong evidence of harm before issuing regulations. Both approaches have critics, but the difference between them comes down to priorities: Is it better to exercise caution at the risk of burdening companies and perhaps the economy, or is it more important to avoid potential economic downsides even if it means that sometimes a harmful product or industrial process goes unregulated? In other words, under what circumstances do we agree to act on a risk? How certain do we need to be that the risk is real, and how many people would need to be at risk, and how costly is it to reduce that risk? Those are moral questions, not scientific ones, and openly discussing and identifying these kinds of judgment calls would lead to a more honest debate. Science matters, and we need to do it as rigorously as possible. But science canât tell us how risky is too risky to allow products like cigarettes or potentially harmful pesticides to be sold â those are value judgements that only humans can make.Studying population involves examining various aspects of the demographic composition, dynamics, and characteristics of a group of individuals within a specific geographic area. Here are key areas to explore when studying population: Demography: Population Size: Analyze the total number of individuals in a given area or community. Population Distribution: Examine how the population is spread across different regions or areas. Population Density: Explore the concentration of people in a particular area relative to the size of that area. Population Growth and Decline: Birth Rate: Study the number of live births per 1,000 people in a given year. Death Rate: Examine the number of deaths per 1,000 people in a given year. Migration: Explore patterns of people moving into and out of a specific area. Age Structure: Age Distribution: Analyze the distribution of individuals across different age groups in a population. Dependency Ratio: Examine the ratio of dependent individuals (young and elderly) to the working-age population. Gender Composition: Sex Ratio: Study the ratio of males to females in a population. Population Pyramids: Use population pyramids to visualize the age and gender structure of a population. Fertility and Family Planning: Total Fertility Rate (TFR): Explore the average number of children a woman is expected to have during her reproductive years. Contraceptive Use: Analyze the prevalence of contraceptive methods in a population. Mortality and Health: Life Expectancy: Examine the average number of years a person can expect to live. Infant and Child Mortality: Study the number of deaths among infants and children under the age of five. Urbanization: Urban vs. Rural Population: Analyze the distribution of people in urban and rural areas. Rate of Urbanization: Explore the speed at which people are moving from rural to urban areas. Education: Literacy Rates: Examine the percentage of the population that can read and write. Educational Attainment: Study the level of education achieved by individuals within the population. Socioeconomic Factors: Income Distribution: Explore the distribution of income among the population. Employment Rates: Analyze the percentage of the working-age population that is employed. Cultural and Ethnic Composition: Ethnic Diversity: Examine the presence of various ethnic groups within the population. Healthcare and Quality of Life: Access to Healthcare: Study the availability and accessibility of healthcare services. Quality of Life Indicators: Explore factors such as housing, sanitation, and overall living conditions. Population Policies and Government Interventions: Study the impact of government policies on population dynamics, including family planning programs and immigration policies. Environmental Impact: Explore the relationship between population growth and its impact on the environment, including resource consumption and pollution. Global Population Trends: Examine global population trends and their implications, including aging populations and population growth in developing countries. Studying population involves a multidisciplinary approach that incorporates elements from demography, sociology, geography, economics, and public health. Researchers and policymakers use this information to make informed decisions about resource allocation, development planning, and social policies.Sociology and ScienceSociology and Social movement theoriesSociology and History QuizPsychology and Sociology and WorldviewsSoc Y2: Sociology and PolicyUCSP Quiz 1 The Nature and Goals of Anthropology, Sociology and Political Science