영어 모의고사 (자동 편성)

Social mobility ①refer to the movement of individuals or families between different positions within a society's system of stratification, whether upward, downward, or sideways. Sociologists distinguish intragenerational mobility, changes within a single person's lifetime, from intergenerational mobility, differences between the social position of parents and their children. A society is often judged by how much intergenerational mobility it permits, since high mobility suggests that outcomes ②depend more on effort and ability than on the accident of birth. Structural mobility, caused by large-scale economic shifts such as the growth of new industries, must ③be distinguished from individual mobility, which results from a single person's particular choices. Research across many nations has found that education ④functions as the primary channel of upward mobility, yet access to quality education is itself unevenly distributed, meaning the very mechanism meant to promote fairness can end up ⑤reproducing the inequality it was designed to overcome.

When engineers design the software that controls a self-driving car, they inevitably face a question that philosophers have debated for ①decades. If a crash becomes unavoidable, should the vehicle protect its own passenger at all costs, or should it be programmed to ②minimize total harm, even if that means steering toward the person inside? Surveys reveal an uncomfortable ③contradiction: most people say a car should be programmed to save the greater number of lives, yet the same people admit they would never buy a vehicle designed to sacrifice its own owner. This gap between the ideal and the personal choice suggests that ethical programming cannot be settled by public opinion alone. Manufacturers, regulators, and philosophers must instead agree on ④transparent rules before autonomous vehicles are ⑤forbidden to make such decisions on the road.

Generative AI systems learn to write, draw, and compose by studying ①enormous collections of existing human work, much of which was created without the artists' knowledge or consent. Supporters of the technology argue that this process resembles how a human student learns by studying the masters, ②absorbing style and technique rather than copying specific pieces. Critics respond that the comparison ③holds up perfectly at scale, since a single AI model can absorb millions of works in days. Courts around the world are now being asked to decide whether training an algorithm on copyrighted material counts as fair use or as ④infringement. Until clearer rules emerge, artists, developers, and publishers remain locked in a legal ⑤gray zone that satisfies almost no one.

Sensors buried in the soil now report moisture levels in real time, drones survey entire fields for signs of disease within minutes, and automated systems adjust irrigation without a farmer ever walking the rows. For large operations with the capital to invest, these tools have ①measurably increased yields while ②reducing water waste, addressing two problems that traditional farming has struggled with for generations. Smaller family farms, however, often ③cannot afford the upfront cost of this equipment, and some worry that the gap between high-tech and traditional operations will only widen as the technology advances further. There is also a quieter cultural cost that rarely appears in productivity reports: generations of farming knowledge risk being ④preserved by dashboards and automated alerts that few young farmers are taught to question, a loss productivity reports rarely ⑤capture.

Emissions trading, a market-based mechanism for curbing greenhouse gases, allows governments to set an overall limit on carbon output while letting firms trade permits within that limit. Under this system, known as cap-and-trade, companies that cut emissions more ①cheaply than required can sell surplus allowances to firms facing higher reduction costs. Proponents argue that this flexibility lets society reach a given environmental target at the ②lowest overall cost, since abatement shifts toward whoever can achieve it most economically. Critics, however, contend that trading schemes frequently allocate too many permits, a flaw that has historically ③depressed carbon prices and blunted incentives to invest in cleaner technology. For example, early phases of several regional markets granted allowances so generously that permit prices ④collapsed, leaving polluters with little pressure to change their practices. Consequently, many economists now advocate combining trading with a price floor, a minimum permit price that keeps the market from collapsing during weak demand, thereby ⑤undermining the cost-effectiveness for which trading is valued.

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

Sociologist Karl Mannheim argued that individuals who come of age during the same historical period tend to share a distinctive outlook shaped by the events, technologies, and crises that defined their formative years, a phenomenon he called a generational unit. (C) This divergence produces what is commonly called a generational gap, most visible when older members of a household interpret a younger relative's habits as a rejection of tradition. (A) Because each generation absorbs its foundational assumptions during adolescence and early adulthood, later generations raised amid different circumstances often develop noticeably different values, even within the same family. (B) Mannheim cautioned against viewing either generation as simply right or wrong, insisting instead that each generation's worldview reflects a coherent response to the particular historical conditions it encountered.

The rejection of unfair offers in the ultimatum game raises an intriguing evolutionary question. (A) One explanation suggests that a willingness to punish unfairness, even at a personal cost, may have conferred long-term advantages within small communities where reputation and repeated interaction mattered greatly. (B) If punishing unfairness is costly in the short term, why would such a tendency have persisted across generations rather than being eliminated by more narrowly self-interested behavior? (C) An individual known to reject unfair offers discourages others from proposing unfair terms in future interactions, ultimately securing fairer treatment over the course of a lifetime.

Convenience installed today, in other words, can quietly become control tomorrow. City governments increasingly market dense networks of surveillance cameras as a straightforward safety upgrade, promising faster emergency response and lower crime rates. ( ① ) In many cases, the technology delivers exactly what it promises, helping investigators identify suspects within hours rather than weeks. ( ② ) Yet the same infrastructure that catches criminals also creates a permanent record of where ordinary, law-abiding citizens go about their daily lives. ( ③ ) Once a camera network exists, its purpose can quietly expand, often without new public debate or explicit approval. ( ④ ) Civil liberties groups argue that a city should decide how much surveillance it wants before the cameras go up, not years afterward when the infrastructure is already impossible to remove. ( ⑤ )

주어진 문장: The same reflexive shift can occur when a smoke alarm suddenly interrupts a deep conversation, even though no one had been monitoring it consciously. Imagine standing at a crowded party where dozens of conversations blend into a wall of noise, yet you effortlessly track the words of the friend beside you. ( ① ) Curiously, if someone across the room utters your name, your attention snaps toward that voice almost instantly. ( ② ) 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. ( ③ ) Early theorists such as Donald Broadbent proposed that unattended information is filtered out entirely before reaching awareness. Yet the fact that a person's own name can break through this filter contradicts such a rigid model. ( ④ ) 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. ( ⑤ ) This refinement suggests that attention operates less like a gate and more like a dimmer switch, adjusting the salience of competing streams of information.