영어 모의고사 (자동 편성)

Consider a village green shared freely by every herder in the community, where each individual may graze as many animals as they wish without ①paying any fee. From the perspective of any single herder, adding one more animal to the shared pasture ②brings a clear personal benefit, since the extra income belongs entirely to that herder alone. The cost of the additional grazing, however, is spread thinly across every herder who uses the green, so no single individual ③bears more than a tiny fraction of the damage. Because this calculation favors adding more animals for every rational herder, the shared pasture is gradually overgrazed until it can no longer ④support any animals at all, harming the very community whose rational members caused the collapse. Philosophers use this scenario to illustrate a troubling gap between what benefits an individual in the short term and what preserves a shared resource in the long term, a gap that voluntary self-restraint alone rarely ⑤closing.

Individuals confronted with a set of options frequently ①default to whichever alternative requires no active decision at all, a tendency scholars term the status quo bias. Rather than weighing the merits of each available choice afresh, decision-makers often treat the current arrangement as a reasonable baseline simply because it already exists, even when ②switching would plainly serve their interests better. This pattern becomes especially apparent in contexts where enrollment in a program ③depend on a default setting. When employees must actively opt into a retirement savings plan, participation rates remain stubbornly low; yet when the same plan is presented as automatic unless an employee opts out, participation rises dramatically, despite the fact that the underlying financial terms ④are identical in both cases. Two forces appear to drive this asymmetry: first, the cognitive effort required to evaluate alternatives, and second, an aversion to the potential regret that ⑤might follow an active decision that turns out poorly.

Imagine rewriting a bacterium's code the way a programmer ①edits a line of software, and much of what synthetic biology promises begins to make sense. Researchers in this field assemble standardized genetic parts into circuits ②that can be inserted into a cell, instructing it to perform a task that no natural organism would carry out. Because these circuits are built from interchangeable parts rather than designed from scratch each time, a circuit tested in one lab can often ③reusing, with minor adjustments, in an entirely different application. Critics note that biological systems rarely behave as predictably as electronic circuits, since a gene ④inserted into a new cell can interact with existing pathways in unexpected ways, occasionally producing results no engineer intended. Even so, as the catalog of standardized parts keeps expanding, engineers are gaining confidence ⑤to design increasingly complex systems, treating the cell as a chassis onto which new functions can be loaded.

When people encounter an individual who appears to memorize enormous quantities of specialized information ①effortlessly, they often assume that person possesses an innate gift. Cognitive psychologists, however, contend that such feats ②rarely stem from raw talent alone. Instead, such feats arise from a learned skill known as chunking, whereby scattered pieces of information are consolidated into larger, meaningful units. A landmark study of chess players demonstrated this principle. When shown a board arranged according to plausible game positions, grandmasters reproduced the layout perfectly. Yet when the same pieces were scattered randomly, their performance ③collapsed to the level of novices. This pattern reveals that expert memory is not larger in raw capacity but is instead organized around patterns accumulated through years of deliberate practice. If chunking, rather than innate aptitude, ④contradicts expert performance, then educators should stop treating talent as fixed and destiny-bound. Curricula ought to be redesigned to cultivate pattern recognition explicitly, since doing so would grant far more students access to expertise once ⑤presumed reserved for the naturally gifted.

People routinely seek out information that confirms what they already believe while ①overlooking or dismissing evidence that contradicts 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 ②taxing to 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 ③unfavorably, while investors who are skeptical of the same company interpret identical news unfavorably, even though both groups are examining the same underlying facts. Social media platforms can ④intensify this effect by algorithmically presenting users with content similar to what they have previously engaged with. Over time, such selective exposure can harden initial impressions into convictions that feel objectively verified, even though they rest on a systematically ⑤filtered sample of evidence.

The immune system produces an almost limitless variety of antibodies, each shaped to latch onto one particular molecular target with remarkable specificity. (A) Monoclonal antibody drugs harness this natural precision by cloning a single antibody-producing cell in the laboratory, generating an army of identical antibodies built to recognize one target, such as a protein on a cancer cell or a molecule driving an autoimmune disease. (B) Because the antibody binds only to its intended target, these drugs tend to spare healthy tissue far more effectively than traditional chemotherapy, which attacks any rapidly dividing cell regardless of whether it is cancerous. (C) Manufacturing monoclonal antibodies remains far more complicated than producing a conventional small-molecule pill, and this complexity keeps monoclonal antibody treatments considerably more expensive than most conventional drugs, a cost that continues to shape debates over pricing and access.

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.

Consequently, even seasoned professionals who believe themselves immune to such influence often fail to notice how much their final judgment has shifted. The anchoring effect can be surprisingly resistant to conscious correction. ( ① ) Even when individuals are explicitly warned in advance that a number they are about to see is randomly generated and therefore meaningless, their subsequent estimates still drift toward that arbitrary figure. ( ② ) This occurs because the mind uses the initial number as a starting point and then adjusts insufficiently away from it, a process that leaves the final judgment biased toward the anchor. ( ③ ) Experimental studies have repeatedly demonstrated this effect across a wide range of tasks, from estimating historical dates to appraising real estate. ( ④ ) The bias persists not because people lack expertise, but because the adjustment process itself is inherently incomplete. ( ⑤ ) Awareness of the anchoring effect, therefore, does not guarantee immunity from it, which is precisely what makes the bias so difficult to counteract in practice.

Several cities have already reported cases in which an innocent person was detained based on a flawed match. Facial recognition software has moved rapidly from airport security lines into shopping malls, schools, and even private apartment buildings, promising convenience in exchange for a quick scan of one's face. ( ① ) Proponents note that the technology can unlock doors, catch shoplifters, and speed up identity checks far faster than any human guard could manage. ( ② ) Independent studies, however, have repeatedly found that many commercial systems perform less accurately on women and people with darker skin tones. ( ③ ) This gap can lead to wrongful identification with serious real-world consequences. ( ④ ) Until these systems can prove equally reliable for everyone, critics argue, deploying them at all represents a form of quiet discrimination dressed up as efficiency. ( ⑤ )

The cell then acts as a temporary factory, translating that instruction into an actual protein without ever altering the cell's permanent genetic code. For decades, most vaccines worked by injecting a weakened or inactivated version of a pathogen, coaxing the immune system into recognizing an enemy it had never truly fought. ( ① ) mRNA vaccines take a fundamentally different route, delivering only a short genetic instruction wrapped in a protective lipid capsule, one that tells the body's own cells how to manufacture a single harmless piece of a virus's outer surface protein. ( ② ) Once those cells display the fragment, the immune system learns to recognize it as foreign and builds a defense, without ever having encountered the actual pathogen. ( ③ ) Because the vaccine contains no live virus and cannot alter a cell's own DNA, developers can redesign the genetic instructions within weeks whenever a pathogen mutates. ( ④ ) This is far shorter than the years-long process required for traditional vaccines. ( ⑤ ) This speed, first proven on a global scale during a recent pandemic, has convinced many researchers that the same platform could eventually be adapted to fight diseases far beyond infectious illness, including certain cancers.