Identifying Primary vs Secondary Sources

Identifying Primary and Secondary Sources

Identifying the Primary Purpose of a Text - Starter Quiz

Instructions: Please answer the following questions to test your understanding of aptitudes and interests. 1. What are Core Drivers (Talents) in the context of aptitudes and interests? a) Abilities that are developed through education b) Natural gifts that predict job effectiveness and contentment c) Interests that change over time d) Personality traits 2. Determine how effective and satisfied you'll be doing a particular kind of work. a) Visual Comparison Speed b) Numerical Reasoning c) Spatial Visualization d) Sequential Reasoning 3. Which Core Driver is associated with the knack for organizing things in a sequential and systematic manner? a) Visual Comparison Speed b) Numerical Reasoning c) Spatial Visualization d) Sequential Reasoning 4. What is the primary role of Space Planners in careers? a) They are responsible for interior design b) They read maps and blueprints c) They generate creative ideas d) They manage financial accounts 5. Which Core Driver relates to the ability to mentally translate two-dimensional images into three-dimensions? a) Visual Comparison Speed b) Numerical Reasoning c) Spatial Visualization d) Sequential Reasoning 6. What type of individuals are known as 3D Visualizers? a) Those who excel in visual art b) People who can quickly process numerical data c) Individuals who can mentally create 3D models from 2D representations d) Creative writers 7. How do Brainstormers differ from Concentrated & Focused individuals in terms of generating ideas? a) Brainstormers generate more ideas b) Concentrated & Focused individuals generate more ideas c) They generate ideas at the same rate d) Both groups struggle to generate ideas 8. What is the primary advantage of having high Visual Comparison Speed? a) It helps in artistic endeavors b) It is useful in complex mathematical problems c) It aids in tasks requiring clerical detail and accuracy d) It enhances spatial visualization 9. Which career is NOT associated with the Core Driver: Visual Comparison Speed? a) Fire Inspector b) Astronomer c) Creative Writer d) Orthoptist 10. What is the main focus of Numerical Reasoning? a) Identifying numerical patterns and trends b) Analyzing historical data c) Solving abstract problems d) Communicating effectively 11. Which Core Driver involves the ability to rapidly draw conclusions from seemingly unrelated pieces of information? a) Numerical Reasoning b) Idea Generation c) Spatial Visualization d) Inductive Reasoning 12. What is the primary characteristic of Diagnostic Problem Solvers? a) They follow a logical step-by-step method of problem-solving b) They rely on specific information and observed experience c) They intuitively leap to conclusions based on limited information d) They are meticulous and deliberate in decision-making 13. What is the role of Fact Checkers in the problem-solving process? a) They intuitively provide solutions b) They rely on specific information and observed experience c) They enjoy acquiring new information and learning d) They make conclusions based on limited facts 14. In what type of role are Abstract Thinkers most comfortable? a) Counseling b) Law c) Marketing d) Construction 15. How can understanding your Core Drivers benefit collaborative work? a) It allows individuals with similar aptitudes to work together more effectively b) It creates conflicts within the team c) It doesn't affect collaborative work d) It makes collaboration more challenging 16. Which Core Driver is associated with processing complex mathematical problems logically? a) Visual Comparison Speed b) Numerical Reasoning c) Sequential Reasoning d) Idea Generation 17. What are Collaborative Planners more likely to do in a team project? a) Lead the team b) Create individual pieces of a project c) Solve abstract problems d) Generate creative ideas 18. How can understanding your aptitudes and interests help you make informed career choices? a) It guarantees job satisfaction b) It allows you to align your career with your strengths c) It helps you choose any career at random d) It has no impact on career decisions 19. Which Core Driver affects whether your thoughts go in several directions at once or follow single ideas more readily? a) Visual Comparison Speed b) Numerical Reasoning c) Idea Generation d) Inductive Reasoning 20. What is the primary characteristic of Idea Contributors? a) They generate creative ideas b) They discuss the big picture and next steps c) They are highly focused and detailed d) They follow a logical step-by-step approach 21. What is the role of Space Planners in the problem-solving process? a) They intuitively provide solutions b) They rely on specific information and observed experience c) They quickly organize information d) They create abstract plans 22. Which Core Driver is linked to the ability to see relationships in seemingly unrelated pieces of information? a) Spatial Visualization b) Inductive Reasoning c) Idea Generation d) Visual Comparison Speed 23. Which career is NOT associated with the Core Driver: Numerical Reasoning? a) Statistician b) Survey Researcher c) Chef d) Actuary 24. What are Core Drivers, and why are they important in the context of aptitudes and interests? a) They are educational qualifications b) They are interests that change over time c) They are natural gifts that predict job effectiveness and contentment d) They are personality traits 25. How can understanding your Core Drivers benefit collaborative work? a) It allows individuals with similar aptitudes to work together more effectively b) It creates conflicts within the team c) It doesn't affect collaborative work d) It makes collaboration more challenging Answers: b) Natural gifts that predict job effectiveness and contentment a) Visual Comparison Speed d) Sequential Reasoning b) They read maps and blueprints c) Spatial Visualization c) Individuals who can mentally create 3D models from 2D representations a) Brainstormers generate more ideas c) It aids in tasks requiring clerical detail and accuracy c) Creative Writer a) Identifying numerical patterns and trends d) Inductive Reasoning c) They intuitively leap to conclusions based on limited information b) They rely on specific information and observed experience b) Law a) It allows individuals with similar aptitudes to work together more effectively b) Numerical Reasoning b) Create individual pieces of a project b) It allows you to align your career with your strengths c) Idea Generation b) They discuss the big picture and next steps c) They quickly organize information b) Inductive Reasoning c) Chef c) They are natural gifts that predict job effectiveness and contentment a) It allows individuals with similar aptitudes to work together more effectively

Time-Telling Quiz: Half Past the Hour Name: ______________________ Date: ______________ What does "half past" specifically mean on an analog clock? A) 15 minutes have passed B) 30 minutes have passed C) 45 minutes have passed D) The hour has just begun When the minute hand points to 6, what position represents "half past"? A) The start of the hour B) Exactly halfway through the hour C) The end of the hour D) A quarter of the way through the hour If the hour hand is between 4 and 5, and the minute hand is on 6, what time is it? A) 4:15 B) 4:45 C) 4:30 D) 5:00 Which statement best describes how the hour hand moves? A) It moves quickly between numbers B) It moves slowly between numbers C) It stays in one place all the time D) It moves only at the top of each hour How many minutes are in a complete circle on a clock? A) 12 minutes B) 24 minutes C) 60 minutes D) 30 minutes When reading an analog clock for "half past", which hand should you look at first? A) The hour hand B) The second hand C) The minute hand D) The decorative hand What is the most important position of the minute hand when identifying "half past"? A) Pointing to 3 B) Pointing to 12 C) Pointing to 6 D) Pointing to 9 If a clock shows half past 7, how would this be written numerically? A) 7:15 B) 7:45 C) 7:30 D) 8:00 Which of the following is TRUE about clock hands? A) The shorter hand always shows minutes B) The longer hand always shows hours C) The longer hand shows minutes, the shorter hand shows hours D) Both hands move at exactly the same speed What is the primary challenge when learning to read "half past" times? A) Remembering the minute hand must be on 6 B) Counting all the numbers on the clock C) Understanding what an hour is D) Knowing the difference between AM and PM Answer Key: B B C B C C C C C A

“There’s No Such Thing as Sound Science” 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 “measuring with precision human activity on the climate is something very challenging to do.” Similarly, Trump’s pick to head NASA, an agency that oversees a large portion the nation’s climate research, has insisted that research into human influence on climate lacks certainty, and he falsely claimed that “global temperatures stopped rising 10 years ago.” Kathleen Hartnett White, Trump’s nominee to head the White House Council on Environmental Quality, said in a Senate hearing last month that she thinks we “need to have more precise explanations of the human role and the natural role” 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 that’s 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 “open science” reform movement that was created, in part, as a response to a “reproducibility crisis” that has struck some fields of science.1 But they’re 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 “sound science.” Science’s virtues are being wielded against it. What distinguishes the two calls for transparency is intent: Whereas the “open science” movement aims to make science more reliable, reproducible and robust, proponents of “sound science” have historically worked to amplify uncertainty, create doubt and undermine scientific discoveries that threaten their interests. “Our criticisms are founded in a confidence in science,” said Steven Goodman, co-director of the Meta-Research Innovation Center at Stanford and a proponent of open science. “That’s a fundamental difference — we’re critiquing science to make it better. Others are critiquing it to devalue the approach itself.” Calls to base public policy on “sound science” seem unassailable if you don’t know the term’s 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 “sound science.” In an internal memo, Philip Morris vice president of corporate affairs Ellen Merlo wrote that the program was designed to “discredit the EPA report,” “prevent states and cities, as well as businesses from passing smoking bans” and “proactively” 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 it’s sometimes represented to the public, science is not a magic wand that turns everything it touches to truth. Instead, it’s 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. “Science is a process rather than an answer,” said psychologist Alison Ledgerwood of the University of California, Davis. Every answer is provisional and subject to change in the face of new evidence. It’s not entirely correct to say that “this study proves this fact,” Ledgerwood said. “We should be talking instead about how science increases or decreases our confidence in something.” The tobacco industry’s 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. “Doubt is our product,” wrote one employee of the Brown & Williamson tobacco company in a 1969 internal memo. The note went on to say that doubt “is the best means of competing with the ‘body of fact’” and “establishing a controversy.” These strategies for undermining inconvenient science were so effective that they’ve 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. It’s also a 1998 action plan by the American Petroleum Institute, Chevron and Exxon Mobil to “install uncertainty” about the link between greenhouse gas emissions and climate change. It’s industry-funded groups’ late-1990s effort to question the science the EPA was using to set fine-particle-pollution air-quality standards that the industry didn’t want. And then there was the more recent effort by Dow Chemical to insist on more scientific certainty before banning a pesticide that the EPA’s scientists had deemed risky to children. Now comes a move by the Trump administration’s EPA to repeal a 2015 rule on wetlands protection by disregarding particular studies. (To name just a few examples.) Doubt merchants aren’t pushing for knowledge, they’re practicing what Proctor has dubbed “agnogenesis” — the intentional manufacture of ignorance. This ignorance isn’t simply the absence of knowing something; it’s a lack of comprehension deliberately created by agents who don’t want you to know, Proctor said.2 In the hands of doubt-makers, transparency becomes a rhetorical move. “It’s really difficult as a scientist or policy maker to make a stand against transparency and openness, because well, who would be against it?” said Karen Levy, researcher on information science at Cornell University. But at the same time, “you can couch everything in the language of transparency and it becomes a powerful weapon.” 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. “Gridlock is the greatest friend a global warming skeptic has,” said Marc Morano, a prominent critic of global warming research and the executive director of ClimateDepot.com, in the documentary “Merchants of Doubt” (based on the book by the same name). Morano’s site is a project of the Committee for a Constructive Tomorrow, which has received funding from the oil and gas industry. “We’re the negative force. We’re just trying to stop stuff.” 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 “quality, objectivity, utility, and integrity of information” 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. “It was passed in this very quiet way with no explicit debate about it — that should tell you a lot about the real goals,” Levy said. But what’s most telling about the Data Quality Act is how it’s 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 “Trojan horse” law that uses the language of transparency as a cover to achieve other political goals. Smith’s 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 can’t 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 it’s not so simple. “There’s a misplaced idea that we can definitively distinguish the good from the not-good science, but it’s all a matter of degree,” said Brian Nosek, executive director of the Center for Open Science. “There is no perfect study.” Requiring regulators to wait until they have (nonexistent) perfect evidence is essentially “a way of saying, ‘We don’t want to use evidence for our decision-making,’” Nosek said. Most scientific controversies aren’t 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. “While 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 ‘the facts’ are.” What’s needed in these cases isn’t more or better science, but mechanisms to bring those hidden values to the forefront of the discussion so that they can be debated transparently. “As 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,” Carolan writes. The dispute over tobacco was never about the science of cigarettes’ 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 isn’t about whether our planet is heating, but about how much responsibility each country and person bears for stopping it. While researching her book “Merchants of Doubt,” 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. “None of this is about the science. All of this is a political debate about the role of government,” 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 — 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 can’t tell us how risky is too risky to allow products like cigarettes or potentially harmful pesticides to be sold — those are value judgements that only humans can make.

Identifying chance outcomes and naming them as fractions

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