What is point of view?

The narrator's perspective or opinion in a story.

The sequence of events in a story.

Which of the following indicates first person point of view?

I walked to school and saw my friends waiting for me.

He looked out the window and saw a rainbow.

She ran to the park and played on the swings.

They went to the beach and built sandcastles.

What is third person point of view?

The narrator tells the story using 'he', 'she', or 'they'.

The narrator tells the story using 'you'.

The narrator tells the story using 'we'.

The narrator tells the story using 'I'.

What is the main purpose of identifying point of view in a story?

To understand how it affects the story and the reader's perspective.

To analyze the main characters in the story.

To determine the sequence of events in the story.

To identify the setting of the story.

Which of the following is an example of third person limited point of view?

Sarah watched the raindrops fall outside the window, wondering if her soccer game would be canceled.

I went on a hike through the mountains, enjoying the breathtaking views.

They sat on the bench, laughing and sharing stories.

We explored the ancient ruins, uncovering hidden treasures.

What is the definition of point of view in literature?

The perspective or vantage point from which a story is told.

The physical location or time period of a story.

The main theme or message of a story.

The order and arrangement of events in a story.

Finding Point of View in 4th grade text.

Create a vocabulary quiz for 10th grade EFL students at CEFR B1 level. For example: adequate means: 1. sufficient 2. more and more 3. not enough. Use all the vocabulary below and provide accompanying definitions per the example to create this vocabulary quiz. The vocabulary quiz must contain at least 226 questions including the following vocabulary: addition advance advanced advertising among other things analysis appear approach as at least average be responsible for something be responsible for doing something before besides can challenge chance change characteristic claim come after come first come last common complicated concern conditions conduct consequence considerable cope critic current decrease delayed deliberately demonstrate design destruction development disagreement disaster discovery dislike do doubt drop educate efficient emphasis enjoyable essay essentially even if even though event exactly except that exist extraordinary feature feedback figure financial finding findings flexible flood flu focus on somebody or something focus frequent fresh frighten from gain generate guidance hopefully ideal illness illustrate image in terms of something in actual fact in connection with something in that case in the meantime initial instruction intelligence interest introduce invest investigate just about just about keep on doing something kind of knowledge lack landscape likely limited little look at something low material mean means measure mention miss misunderstand more or less must naturally nature necessarily nevertheless not at all not only notice objective occasional official on the one hand on the other hand once others otherwise out of date participate particular past perform personality personally planet planning plant point of view policy pollution popular population prevent priority private probable produce profession professor proof proposed protest provided (that) psychology public purpose quality question question questionnaire react reasonable recommend recycle regard region regular relevant reliable rely on/upon sb/sth request research result review revise risk run out of rural salary sample seldom sense set up sth or set sth up significant skilled slight specialist specific still structure study supposed surface take advantage of sth thanks to somebody or something theory throw away throw out something throw something away throw out transport trash treatment unfortunately unhealthy unique united universe unknown unlike unlikely urban vary view visible vision volume whom wildlife within worthwhile would additional analyze analyst appearance on average change characterize complicate concerned concerning concerned with something consequently cope with something criticize criticism currently deliberate demonstration designer developing developed educated educator efficiency efficiently emphasize enjoyment existence existing figure out something finance flexibility frequency hopeful illustration initially intelligent interested in something investor investment investigation investigator limitation meaning occasionally old-fashioned participant participation particularly performance planned pollute prevention producer professional psychological psychologist publicly reaction reasonably recommendation regardless regarding regional relevance researcher resulting revision sensible set out something set something out significantly significance skillful slightly specialize specifically specify theoretical transportation unfortunate unity unite universal variation viewer

Match the word to its synonym level B1 CEFR. Use the vocabulary exactly adverb precisely except that aside from exist verb to be real existing adjective real, current Example: Flying cars are not practical with existing technology. existence noun reality Example: The existence of black holes has been confirmed by indirect observation. extraordinary adjective unusual feature noun important part of something Example: The Ramon Crater is a unique feature of the Negev Desert. feedback noun reaction figure noun shape Example: I can’t tell if that figure in the shadows is a man or a woman. figure out verb understand Example: I just can’t figure out how the magician did that amazing trick. financial adjective related to money Example: Her family is having financial problems so they can’t travel overseas this year. finance verb pay for Example: If I can’t get a loan from the bank, I won’t be able to finance a new apartment. finance noun money Example: An expert in finance predicts a global recession. finding/findings noun discoveries; results of a study Example: According to the findings of the police investigation, this is the gun which fired the fatal bullet. flexibility noun willingness to change flexible adjective adjusts easily Example: I’d prefer to meet on Monday morning but I can be flexible depending upon your schedule. flood noun a lot of water flood verb to cover with too much water flu noun type of sickness focus on/upon verb pay attention to Example: You should focus on your schoolwork if you want to improve your grades. focus noun attention People with attention deficit disorder lose focus easily. frequency noun how often frequent adjective very often Example: Hanah is a frequent customer and everyone at the store knows her. fresh adjective new Example: We need some fresh ideas if we’re going to solve this problem. frighten verb scare from preposition position, starting point gain verb make an increase, profit, earn Example: I have nothing to gain by choosing sides so I shall remain neutral. gain noun profit, amount earned generate verb create, make Example: Chat GPT can generate text written in any style you choose. guidance noun help, advice hopeful adjective optimistic, having a positive outlook Example: The farmers are hopeful that we will have rain this winter. hopefully adjective with luck ideal adjective best, most preferable Example: Nuclear power may not be an ideal solution to global warming, but it’s certainly worth considering. illness noun sickness, disease illustrate verb draw pictures illustration noun picture, image Example: Children’s storybooks have colorful illustrations. image noun picture, especially on film or television Example: The mother of the pop singer cried when she first saw her daughter’s image on television. in preposition within, inside, into in terms of regarding Example: That company makes a great product but they’re lacking in terms of customer service. in actual fact in truth Example: The mayor says the city is a safe place to live, but in actual fact the violent crime rate is very high. in connection with about Example: Police arrested four men in connection with the robbery. in that case if that is true Example: Billy Bob: “Traffic could be heavy tomorrow.” Peggy Sue: “In that case, we better leave early.” in the meantime while, during Example: The new computers won’t arrive until next week, but we can keep using the old ones in the meantime. initial adjective first Example: Her initial reaction to that song was negative, but over time she’s come to like it. initially adverb at first instruction noun teaching, order Example: Most new electronic devices come with a set of instructions. intelligence noun smartness Example: Since you have a degree from a good university, I assume you have sufficient intelligence to understand this problem. intelligent adjective smart Example: Joe isn’t very intelligent, but he is a kind person with a warm heart. interest noun attraction Example: Yossi has little interest in politics, whereas his wife goes to all the protests and demonstrations. interest verb to attract Example: Sports don’t really interest me, but my brother is a big basketball fan. introduce verb to show something new Example: Today in class I will introduce the basic concepts of literary analysis. invest verb to put money into something in order to earn money Example: Joe invested in cryptocurrency and lost a lot of money. investor noun one who puts money into something in order to earn money Example: Venture capitalists are investors who put money into risky start-up businesses. investment noun putting money into something in order to earn money Example: Buying real estate in Israel is a very safe investment because the value never goes down. investigate verb research, study Example: The police collected evidence to investigate the murder. investigation noun study Example: The police don’t have a suspect for the murder as the investigation isn’t finished yet. investigator noun detective Example: Detective Schmendrick is the lead investigator for the murder case. just about almost Example: I’m just about done here so I’ll be there shortly. keep on doing verb continue Example: You’re crazy if you keep on doing the same thing and expect different results. kind of type of Example: What kind of dog is that, a poodle? knowledge noun awareness Example: John failed the test due to lack of knowledge of the material. lack verb not having, missing Example: John failed the test due to lack of knowledge of the material. landscape noun the view of the land likely adjective, adverb probably Example: When we learn from our mistakes, we’re not likely to forget. limited adjective restricted Example: We should go to the store today because the sale is for a limited time only. limitation noun restriction little adjective small, not a lot Example: She always tells the truth. I have little reason to doubt her. look at verb see Example: People used to read newspapers on the train. Nowadays they just look at their phones. low adverb to a small amount or level Example: I have to charge my phone because the battery is running low. material noun documents, information Example: We have a lot of material to cover before the end of the semester. meaning noun significance mean verb to have significance or purpose means noun form of, by the use of Example: They communicate by means of radio. measure noun step Example: The teacher took measures to prevent cheating during the test mention verb to say, point out Example: The coach said the team played very well today but didn’t mention any player specifically. miss verb (1) fail to catch (2) wishing to see somebody Examples: (1) The football player kicked the ball but missed the goal. (2) Wow, it’s good to see you! I’ve missed you so much! misunderstand verb understand incorrectly Example: I’m afraid I misunderstood the instructions. Could you repeat them please? more or less approximately, somewhat, to a varying degree Example: This is more or less a religious neighborhood, though there are a few secular families. must modal verb have to naturally adverb as expected, normally nature noun (1) open air (2) character Examples: (1) We like to go hiking in nature reserves. (2) Pit bulls are aggressive by nature.

Got a presentation to make? Easy enough. Think of this as an opportunity to convince someone to see your point of view. One effective way to do that is by using data. Data is facts, numbers, and figures used to report the results of the research. Using data can be helpful to explain complex subjects. Here's how to do it. Research your topic to find data to support your presentation. Step 2. Be sure that any facts or figures you use are from reliable sources, like government, university, and scientific websites or trusted news outlets. You have to be careful. There is a lot of fake information floating around. Step 3. Take the time to edit your data so you're only using what's important and relevant to your topic. Reciting a long list of facts and numbers can put your audience to sleep. Step 4. Remember your data has to tell a story. Choose the right words and phrases to describe your findings. Reports indicate a sharp decrease in costs. Step 5. Take your facts and numbers and turn them into something exciting. This chart shows we had a boom in exports. Almost any data can be used to create colorful and eye-catching graphics and charts. In this graph, you can see a dramatic increase. Which makes it more memorable and 100% more entertaining to watch. Thank you.

Stages in the Sale of a Property Stage 1 – Getting to Instruction • Initial contact with the vendor: need to check the following: type of property, contact details of vendor, address of property/Eircode and purpose of the contact - sale or valuation? If a sale, does the vendor need a quick sale? Qualify the lead i.e. is the vendor buying another property? If an investment property, is the tenant in situ? Check if there is a folio number available and confirm the ownership of the property. Schedule the viewing. • Pre-viewing: Set up a file & record all info from initial contact on CRM system. Check the Property Price Register to help get a general idea of property valuation (subject to viewing, helps to display knowledge of area/market and set expectations for the vendor). Nature of property may affect pricing e.g. starter home vs. larger property with vendor seeking to downsize. Consideration for comparables may include similar/same location, size and condition of property, availability and type of parking, layout of property, plot size, orientation of garden, extensions undertaken etc. Nature of market conditions, state of wider economy, cost of capital and availability of credit may also be factors. • Appraisal/viewing: Bring an advertising pack/sales & marketing brochures. Walk through property with client, note nice features/selling points for the brochure, let the client talk about upgrades/specific features of the property. It is very important to listen to the vendor and build rapport. Confirm property details e.g. condition and layout, plot size, orientation of garden. Check for certificates of compliance for any extensions, planning permissions for conversions, right of way if applicable etc. Check if a BER available/provide details for approved assessors. Demonstrate your/the practice’s professional expertise, justify why you should get the instruction, discuss recent local sales and give your potential valuation. Discuss the sales fee, marketing fee and any additional charges e.g. professional photography, drone footage, virtual tours (walkthrough video, Matterport etc.) Ask how the vendor heard about you/your practice and why are they considering you for the sale. Where appropriate offer advice to help vendor increase potential sales price. (If possible, leave with signed Property Services Agreement/Letter of Engagement.) Thank you, send/email market appraisal, any queries/questions do get in touch and let the vendor know that we’ll be in touch in coming days. • Post appraisal – letter sent that pm/next morning with market appraisal; diary note to follow up. Check that market appraisal letter received and check for questions. If did not get sale, find out why not/debrief. If get the sale, email confirmation of instruction. Once PSRA sent and LOE returned signed = stage 2. Other details required – ID, proof of address, proof of ownership/title, solicitor details, BER certificate (refer to assessor if not available). All these should be uploaded to CRM. Stage 2 – Getting to ‘Sale Agreed’ Set up appointment to measure & photograph, note any special features e.g., upgraded kitchen, south-facing garden. Provide ideas for improving sales potential (declutter, painting, tidy garden etc. Check if has vendor potential buyers in mind already e.g., relations, friends, other parties interested. Seek vendor approval for photos/text of brochure. Check for access (tenants in situ/working from home etc) and confirm viewing times. If given a key for viewings – tag it! Check alarm codes & whether a sign is allowed on the property. Bring to market – upload to all websites e.g., daft/my home, in house websites and create window display. Match the property against your internal database of potential purchasers /CRM system. Set up appointments for viewings on CRM or arrange for open viewings. Confirm viewings with vendor & purchaser. Turn on lights, open windows, secure valuables, leave out brochures & business cards, bring viewings sheets to keep record of attendees. Introduce yourself and get attendee details. Let people view the property and address any questions. Point out key features. Record questions to be answered and any feedback from viewers. Ask are they selling property? Let viewers know of offers already received. Lock up/alarm property/close windows. Provide vendor with feedback on viewings - number of viewers / questions raised/overall reaction to property. Offers should be confirmed in writing & upload to on CRM/ offers will be input by bidders onto online bidding platforms ‘Proof of funds’ required for offers in some practices. Successful bidder will be chosen by vendor, who might want quick sale/no chain or prefer the highest bidder. Booking deposit will be sought from successful bidder. The amount varies by practice but must cover fees. Sales Advice Notice/letter should be sent to both solicitors (and may be cc’d to vendor/buyer or notify both that SAN have gone out). Booking deposit receipt should be issued. The BER certificate and report should go to the solicitor. Send requests for docs/info to successful bidder including steps they need to take to progress sale e.g., organise the bank valuation and/or schedule the survey. Once the deposit is paid the property is Sale Agreed, inform other bidders, and update all websites/sales board etc. Stage 3 – Getting to closing Access should be organised for the bank valuation/survey. Stay in touch with both solicitors ‘contract-chasing’ i.e., check when contracts are issued, signed and queries answered. Legal searches undertaken by the solicitors may include checking boundaries, land registry, title, rights of way, compliance certs etc. When contracts are signed 10% purchase price/booking deposit should be sent to the vendor’s solicitor. Once all queries satisfied = drawdown of mortgage/funding, house/life insurance in place. Title deeds will be requested once contract is signed. Decide final closing date. Check that the property taxes have been paid. Check that vendor has vacated the property. When vacant, conduct the final walkthrough and take final readings (MPRNs ). Check with solicitor if the drawn down funds h, and once received the solicitor gives authorisation to the estate agent to release the keys. The agent will do up invoice, send the balance of funds to solicitor and provide gift to purchaser. Finally remove sign, mark as sold on CRM, seek testimonials, upload to social media and close a/c on CRM

Steps in Thematic Analysis.Step 4: Reviewing themes Now we have to make sure that our themes are useful and accurate representations of the data. Here, we return to the data set and compare our themes against it. Are we missing anything? Are these themes really present in the data? What can we change to make our themes work better? If we encounter problems with our themes, we might split them up, combine them, discard them or create new ones: whatever makes them more useful and accurate. For example, we might decide upon looking through the data that “changing terminology” fits better under the “uncertainty” theme than under “distrust of experts,” since the data labelled with this code involves confusion, not necessarily distrust. Step 5: Defining and naming themes Now that you have a final list of themes, it’s time to name and define each of them. Defining themes involves formulating exactly what we mean by each theme and figuring out how it helps us understand the data. Naming themes involves coming up with a succinct and easily understandable name for each theme. For example, we might look at “distrust of experts” and determine exactly who we mean by “experts” in this theme. We might decide that a better name for the theme is “distrust of authority” or “conspiracy thinking”. Step 6: Writing up Finally, we’ll write up our analysis of the data. Like all academic texts, writing up a thematic analysis requires an introduction to establish our research question, aims and approach. We should also include a methodology section, describing how we collected the data (e.g. through semi-structured interviews or open-ended survey questions) and explaining how we conducted the thematic analysis itself. The results or findings section usually addresses each theme in turn. We describe how often the themes come up and what they mean, including examples from the data as evidence. Finally, our conclusion explains the main takeaways and shows how the analysis has answered our research question. In our example, we might argue that conspiracy thinking about climate change is widespread among older conservative voters, point out the uncertainty with which many voters view the issue, and discuss the role of misinformation in respondents’ perceptions.

“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.

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