영어 모의고사 (자동 편성)

Among the many tools available to those who design choice environments, few are as quietly powerful as the default option, the alternative that ①takes effect automatically unless a person actively selects something else. Because changing a default requires deliberate effort, many individuals simply accept whatever arrangement has been preselected for them, regardless of whether that arrangement actually ②serve their interests best. This tendency has been documented across a remarkably wide range of contexts. Countries that automatically enroll citizens in organ donation programs, requiring an explicit request to opt out, consistently report far higher donor registration rates than countries that require citizens ③to actively opt in. Employers who automatically enroll new hires in retirement savings plans likewise see participation rates ④climb dramatically compared with employers who leave enrollment entirely voluntary. What makes default options so influential is not merely convenience; a default also functions as an implicit signal about what is considered normal or recommended, subtly ⑤shaping perceptions even among individuals who believe themselves to be deciding independently.

Over the past two decades, insights drawn from behavioral economics have moved beyond academic journals and into the machinery of government itself, ①reshaping how numerous public programs are designed and implemented. Tax authorities in several countries, for example, discovered that simply informing citizens how many of their neighbors had already paid overdue taxes on time substantially ②increased subsequent compliance rates, outperforming letters that merely threatened legal penalties for continued nonpayment. Public health agencies have applied similar principles to encourage preventive care, finding that appointment reminders phrased to emphasize the personal cost of a missed visit ③proved more effective than neutral reminders listing only the date and time. Employment offices redesigned job-seeking assistance programs around specific, actionable steps rather than general encouragement, discovering that participants who were asked ④to write down a concrete plan for the following week were considerably more likely to follow through than those who received only general advice. What unites these disparate interventions ⑤are a shared recognition that small, carefully tested adjustments to how choices are presented can produce measurable improvements in outcomes.

Behavioral economists have long observed that people tend to feel the pain of losing something more intensely than the pleasure of gaining an equivalent amount, a tendency ①known as loss aversion. This asymmetry, which ②was first documented through a series of carefully designed experiments, suggests that the psychological weight of a loss can be roughly twice that of a comparable gain. Consider an investor who refuses to sell a declining stock, ③clings to the hope that its price will eventually recover, even when all available evidence indicates that selling and reinvesting elsewhere would be more rational. Such behavior, though it ④appears irrational from a purely economic standpoint, becomes understandable once we recognize that the investor is trying to avoid the sharp discomfort associated with realizing a loss. Similarly, consumers often demand a much higher price to give up an item they already own than they would be ⑤willing to pay to acquire the same item in the first place.

Social unrest does not always emerge from the poorest conditions; it frequently erupts when circumstances ①are improving but not quickly enough to satisfy rising expectations. This paradox lies at the heart of relative deprivation theory, which ②holds that discontent arises less from objective hardship than from a perceived gap between what people expect and what they actually receive. Political scientist Ted Gurr illustrated the pattern with what is often called the J-curve: revolutions tend to follow a period of sustained improvement that is then followed by a sudden reversal, ③left citizens who had grown accustomed to progress feeling suddenly cheated of gains they had come to regard as their due. Because the theory centers on perception rather than raw statistics, it helps explain why relatively prosperous societies can experience intense protest while societies ④mired in long-standing poverty sometimes remain comparatively quiet, ⑤having adjusted their expectations to match a bleak and unchanging reality.

Millions of people now wear devices that continuously track their heart rate, sleep patterns, and daily activity, generating an ①intimate stream of health data that would have been unthinkable to collect just two decades ago. Users generally assume this information belongs to them, since it is drawn directly from their own bodies. In practice, however, the terms of service that few people read often grant the manufacturer ②narrow rights to store, analyze, and even sell anonymized versions of that data to insurers or advertisers. This arrangement becomes especially troubling when health data influences decisions far beyond fitness, such as insurance premiums or employment screening. Advocates for reform argue that biological data deserves a category of protection ③stronger than ordinary consumer information, precisely because it can never truly be ④replaced or reset once it has been ⑤exposed.

A striking proportion of individual investors believe their own stock-picking ability to be above average, a statistical ①impossibility given that only half of any population can genuinely outperform the rest, yet a pattern that persists with remarkable consistency across surveys. This tendency, known as overconfidence bias, leads investors to trade more ②frequently than a more cautious assessment of their own skill would justify. Extensive research comparing the trading records of numerous individual accounts has ③demonstrated that investors who trade most frequently tend to earn substantially ④higher returns than those who trade rarely, largely because transaction costs accumulate and because frequent trading often reflects overconfident reactions to short-term noise rather than genuine insight. Overconfidence also manifests in the tendency to underestimate the range of possible outcomes, causing investors to concentrate their holdings in a small number of assets they feel certain about rather than diversifying across a broader portfolio. Paradoxically, then, the very confidence that motivates investors to act decisively often ⑤undermines the outcomes they are trying to achieve.

When people estimate the value of an unfamiliar product, they rarely rely on objective calculation alone; instead, they anchor their judgment to whatever numerical reference happens to be presented first, however ①arbitrary that number may be. This phenomenon exerts a ②disproportionate influence on price perception precisely because initial figures function as a kind of cognitive gravity that subsequent estimates struggle to escape. A shopper who first sees a jacket listed at $300 before it is marked down to $150 will likely judge the discounted price as an excellent ③bargain, regardless of whether $150 actually reflects the jacket's true worth. Retailers, well aware of this bias, frequently display a ④deflated "original price" beside a discounted one, not because the higher figure is meaningful, but because it recalibrates customers' expectations. Even professionals are not immune: negotiators who open with an extreme initial offer often secure more ⑤favorable final terms than those who begin with a moderate one.

Financial markets occasionally experience episodes in which asset prices rise far beyond any level that careful analysis of underlying fundamentals could justify, a phenomenon commonly attributed to herd psychology. During such episodes, individual investors, observing that prices have already risen substantially, often conclude that continuing to buy is ①reasonable simply because so many others are doing the same, rather than because any independent evaluation supports the purchase. This dynamic can become self-perpetuating: rising prices attract new buyers, whose purchases push prices higher still, thereby attracting yet another wave of buyers convinced that the upward trend itself constitutes ②reliable evidence of underlying value. Historical episodes of speculative excess display a strikingly similar pattern, suggesting that the underlying psychological mechanism remains ③variable even as the specific assets involved change considerably across centuries. Eventually, however, some triggering event, however minor, prompts a portion of investors to ④reconsider their assumptions, and the resulting wave of selling can trigger a collapse every bit as rapid and self-reinforcing as the original ⑤ascent.

As more schools shift toward digital textbooks and online assignments, a student without reliable internet access at home faces a disadvantage that has little to do with talent or effort. During recent years, this gap became ①impossible to ignore, as families in rural areas or low-income neighborhoods struggled to complete schoolwork that assumed a stable connection and a personal device. Some policymakers initially treated internet access as a ②convenience, comparable to cable television, rather than as infrastructure essential to modern life. That assumption is increasingly being reconsidered, particularly as more essential services move online by default. Closing this divide will require ③far less than simply distributing devices; it will demand ④sustained investment in the physical networks that carry information into every home, ⑤regardless of income or location.

Facing a shortage of caregivers and a rapidly aging population, several countries have begun deploying robots designed to remind elderly residents to take medication, monitor for falls, and even offer simple conversation throughout the day. Early trials show that many residents report ①reduced loneliness, particularly when a robot's presence allows an overworked human staff member to spend a few extra minutes with each patient rather than rushing between rooms. Critics, however, worry that this framing quietly ②shifts the goal of care: instead of asking how technology can support human connection, institutions may come to treat a robot's companionship as an ③unacceptable substitute for it. Advocates for the elderly argue that robots should be evaluated strictly as tools that free up human time for human contact, ④never as a lower-cost replacement for the contact itself, since human presence remains ⑤irreplaceable.