영어 모의고사 (자동 편성)

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.

People routinely seek out information that confirms what they already believe while overlooking or dismissing evidence that ①contradicts those beliefs, a pattern known as confirmation bias. This tendency operates not because individuals are deliberately dishonest, but because the mind finds it cognitively less taxing ②to absorb information that fits an existing framework than to reconstruct that framework from scratch. Investors who believe a particular company will succeed, for instance, tend to interpret ambiguous news about that company favorably, while investors who ③are skeptical of the same company interpret identical news unfavorably, even though both groups are examining the same underlying facts. Social media platforms can intensify this effect by algorithmically presenting users with content similar to what they have previously engaged with, thereby ④narrowing the range of perspectives an individual regularly encounters. Over time, such selective exposure can harden initial impressions into convictions that ⑤feels objectively verified, even though they rest on a systematically filtered sample of evidence.

The discovery of CRISPR gene-editing technology gave scientists a tool precise enough ①to correct a single mistaken letter in the human genome, raising hope for curing inherited diseases that have resisted treatment for generations. Yet the same precision that makes CRISPR so promising also makes it dangerous in the wrong hands. Editing a gene in a sperm, egg, or early embryo does not simply change one patient; it alters the genetic code ②passed down to every future generation, a decision no single person should ③allow to make alone. Scientific organizations around the world have therefore drawn a careful line, ④permitting gene editing to treat disease in existing patients while banning any edit that would be inherited by their descendants. Critics worry, however, that this line will become harder to enforce than it ⑤is to draw.

Imagine standing at a crowded party where dozens of conversations blend into a wall of noise, yet you ①effortlessly track the words of the friend beside you. Curiously, if someone across the room utters your name, your attention snaps toward that voice almost ②instantly. This happens even though you had not consciously been listening to that conversation at all. This phenomenon, known as the cocktail party effect, reveals that selective attention does not simply block out every unattended sound. Early theorists such as Donald Broadbent proposed that unattended information is ③filtered out entirely before reaching awareness. Yet the fact that a person's own name can break through this filter ④contradicts such a rigid model. Anne Treisman later refined this account, suggesting that unattended channels are merely attenuated rather than eliminated altogether. Especially meaningful stimuli, including one's own name, can still surpass the threshold of conscious recognition. This refinement suggests that attention operates less like a gate and more like a dimmer switch, ⑤ignoring the salience of competing streams of information.

German sociologist Ferdinand Tönnies distinguished between two fundamentally different forms of social organization, which he termed Gemeinschaft and Gesellschaft. Gemeinschaft, often translated as community, describes relationships bound by close kinship, shared tradition, and face-to-face familiarity, ①typical of small villages where individuals know one another across an entire lifetime. Gesellschaft, often translated as society, describes relationships organized around ②impersonal contracts, self-interest, and formal law, typical of large cities where interactions occur between relative strangers who cooperate for specific, limited purposes. Tönnies did not regard one form as simply superior to the other; rather, he saw the shift from Gemeinschaft toward Gesellschaft as a defining feature of modernization, one that brought greater efficiency and individual freedom while ③strengthening the dense emotional bonds that once held communities together. Contemporary sociologists continue to debate whether digital networks represent a genuine ④revival of Gemeinschaft-style community or merely extend Gesellschaft's impersonal logic into new, more ⑤intimate-seeming spaces.

Millions of people now wear devices that continuously track their heart rate, sleep patterns, and daily activity. 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 broad rights to store, analyze, and even sell anonymized versions of that data. Advocates for reform argue that biological data deserves a category of protection stronger than ordinary consumer information, precisely because _______________.

Factories that once employed hundreds of workers on an assembly line now run with a fraction of that staff, as robotic arms handle tasks that used to require human hands. (A) However, critics point out that earlier transitions unfolded over generations, giving workers time to retrain, whereas today's robots are being deployed much faster. (B) Historical evidence offers some comfort: previous waves of automation eventually created new categories of work that no one had predicted. (C) A factory worker displaced this year, therefore, cannot simply wait for a new industry to emerge decades from now.

Philosophers sometimes ask their students to imagine a creature physically identical to an ordinary human being in every measurable respect, one that walks, talks, laughs, and even cries out in apparent pain when injured, yet that has no inner conscious experience whatsoever. (A) Critics respond that mere conceivability proves very little about what is genuinely possible in the real world. (B) This imagined being, commonly called a philosophical zombie, behaves exactly as a conscious person would, since every neuron fires in precisely the same pattern. (C) Defenders of the argument claim that because such a zombie is at least conceivable without any logical contradiction, consciousness itself cannot be fully explained by physical processes alone.

Hospitals are increasingly adopting artificial intelligence tools that can scan medical images and flag potential tumors faster than experienced radiologists. (A) The doctor may argue that they simply trusted a tool the hospital required them to use, while the hospital may blame the software company instead. (B) Yet the growing reliance on these tools raises an uncomfortable legal question: when an AI system misses a diagnosis, who is responsible? (C) Until legal systems clarify this chain of responsibility, patients harmed by an algorithmic error may find themselves with no clear party to hold accountable.

Yet this reluctance to accept a small certain loss often leads to a much larger loss later, when the declining trend continues unabated. Loss aversion strongly influences how investors manage their portfolios during periods of market decline. ( ① ) When the value of a stock begins to fall, many investors postpone selling, hoping that the price will rebound to its original level. ( ② ) This tendency is closely tied to the psychological discomfort of converting an unrealized loss into a realized one, since selling forces the investor to formally acknowledge the loss. ( ③ ) Research on trading behavior consistently shows that investors hold declining stocks for longer periods than rising ones, a pattern that runs counter to the basic principle of cutting losses early. ( ④ ) Financial advisors therefore encourage clients to set predetermined selling thresholds in advance, before emotional attachment to a particular price can distort their judgment. ( ⑤ ) By committing to a rule beforehand, investors can partially neutralize the emotional bias that loss aversion introduces into decision-making.