Reading Comprehension for Bank Exams, Reading Comprehension for Bank PO, RC for Bank PO, RC for bank exams

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Reading Comprehension for Bank Exams

This is the 10th set of the Reading Comprehension series for bank and insurance exams. Reading Comprehension plays an important role in the English section of banking exams. Because English is not subject it should be treated as a language and for this, we should read English regularly in any form like an editorial, or story.

This post is for the bank exam candidates preparing for bank exams like SBI PO, IBPS PO, and RRB PO. If any candidate has any doubt regarding any question or topic, he/she can comment in the comment section provided below the post. Our every reading comprehension post contains 2 prelims levels and one main level passage. The aim of our platform is to provide free content that is available on Google to those students who are preparing for the banking sector.

Set.1- Does success beget success? Not necessarily. In fact, success can hurt a winning team. In our research, we found that success comes with a trap: It can cause teams to rely more on their most influential members or stars—in other words, the hierarchy of the team becomes steeper. This makes the team less adaptable and more likely to get stuck in old ways of doing things. And, ultimately, it increases the chances of failure the next time around. To investigate how team dynamics worked, we started by looking outside the world of business—at basketball. In our study, published in Organization Science, we examined competitive teams in the National Basketball Association across more than 60,000 games, spanning 34 years. Leveraging motion-tracking-camera data, we examined how teams’ passing patterns and shot distributions changed after wins and losses.

We found that after winning, teams became more reliant on their star players. Teams passed the ball about 6% more to the stars, and their shot distribution skewed 15% more toward the big performers. Although doubling down is intuitive (“We want to exploit what worked before"), it ended up decreasing teams’ chances of winning the next game. The increased reliance on the star players made teams more predictable to the next opponent and easier to defend—and therefore less likely to win the game. This tendency to stick with stars doesn’t just hold true in competitive sports. All teams—particularly ones in the business world—tend to double down on what has worked. And it is often a bad idea. Next, we looked at teams more commonly found in organizations and how they make their choices. We recruited participants to engage in several rounds of decision-making tasks as three-person teams. In each round, only one person could make the team’s final call.

Unbeknown to participants, we randomly manipulated their feedback: Some teams were told they were performing very well after they made a decision; others were told they were performing very poorly. Then they were asked who would make the decision for the team in the next round.

The results: Participants whose team succeeded doubled down on the person who previously held the most influence—giving them 30% more influence over decisions in the next task as compared with teams that lost. We didn’t look specifically at how those teams with a steeper hierarchy performed. But a large body of research supports the idea that a steep hierarchy has a negative impact. One study, for instance, meta-analyzed 54 existing studies spanning more than 13,000 employees and found that overall, team hierarchy is negatively associated with team effectiveness—teams with a steeper hierarchy display lower performance. Together, our two studies suggest that success threatens teams. What can leaders do? We have three evidence-based recommendations:

Build an egalitarian culture: In our research, we found that teams were less likely to fall into the “success trap" when they began with a relatively egalitarian distribution of influence. When egalitarian teams succeed, the credit is less likely to focus on specific performers, but rather on the team. Likewise, blame is less likely to be attributed solely to the stars, so the team can get a clearer picture of what went wrong. But managers need to keep a close eye on teams to make sure they are as egalitarian as possible. Sometimes factors irrelevant to expertise—such as gender, ethnicity, personality, or socioeconomic background—can bias people’s perceptions of who is an expert and who deserves influence. Team leaders need to deliberately provide avenues of influence for more marginalized or socially reserved members.

For instance, research on leading animation studios found that sustained success came from creating norms that allow any member to provide input, even on areas outside their traditional domain of expertise. Review your results: After a project, teams should hold a structured review of what happened and why. Research shows that a 30- to 60-minute debrief—a system pioneered by the military—can help teams highlight the interdependent contributions of all team members. This helps teams develop a more accurate understanding of why things worked and avoid erroneously doubling down on certain members or processes. Such debriefs be especially helpful in learning from success and improving team effectiveness more than many more costly training programs such as managerial training and employee-error-management training.

Think long term: Our research found that a strong desire to immediately repeat short-term success may hurt the team by creating more inequality in influence. Because the goal is to succeed again soon, the team doubles down on the stars that got results the last time—making the team more rigid and less adaptable. For instance, when leaders are focused on the near term, they become less likely to listen to opinions and feedback from nonstar employees—12% less likely than when the teams were oriented to the long term, our research found. To achieve sustained success, managers must move the focus away from short-term success—which can lead to rigidness—and set longer-term goals, which allows teams to remain flexible and versatile. That means taking the focus away from short-term success to redefine teams’ time frame, giving the teams time to experiment and learn, and giving employees the opportunity and incentive to take risks.

Set.2- You’re standing in the polling booth, crisp ballot paper in hand, a dozen or more names printed across it. Many of them you’ve never encountered before. The cross you put next to one of them, however, will shape the government for years to come. How do you choose?  It is a conundrum faced by voters in democratic elections all over the world. Usually, it will come down to a combination of party loyalty, one or two memorable policies, and how you think your friends and family will vote. To politicians’ dismay, the electorate can be incredibly fickle, basing their decision on a candidate’s haircut or how attractive they are, a recent news story, or the desire to “send a message” to those in power. Making an informed choice in the voting booth requires a great deal of investment – reading up on every candidate, and weighing their relative merits against one another. Most people don’t have that kind of time. Voters in the world’s largest democratic elections in India, for example, had to choose from more than 8,039 candidates nationwide from 650 different parties in polling split into eight phases. After all, machines make all kinds of difficult decisions for us. Recommendation engines find us the cheapest flights, the best car insurance, and the optimum mobile phone package, serve our advertisements for things we didn’t know we wanted, find us books to read, movies to watch, suggest gift ideas, and curate playlists of our favorite artists. We even let machines shortlist our romantic prospects. So can artificial intelligence find our perfect match when it comes to political candidates?  One algorithm created by Zeliha Khashman, a researcher in international relations at the Near East University in Nicosia, Cyprus, claims to be able to predict how US Members of Congress will vote on national issues by combining their public opinions with their party affiliation. But Beth Singler, an AI researcher at the University of Cambridge, warns against investing too heavily in their predictive power. “If you have someone running in a presidential election, the candidate may never have been president before, so you can’t say they’ll act in the way that they, or their data, predict,” she says. “You can’t say that people would definitely act in a certain way – people are messy.” 

There’s another problem: when I look into the algorithmic mirror, I might not like what I see. Political identity is important to many of us, and discovering that our political alignments are different from what we believe them to be could be hard to swallow. For example, it would be disconcerting to find out that your views and online behavior mark you out as a conservative when you believed that, like your friends and family, you inhabited the left of the political spectrum. 

This is important, as artificial intelligence increasingly plays a role not only in determining which political candidates the public is exposed to but also in what we don’t see. Social networks are increasingly reliant on AI to root out inaccurate and fraudulent information posted online in the run-up to elections. Already accused of allowing this sort of interference to mar the UK referendum and the 2016 US Presidential election, Facebook is working to make its networks more resilient to bad actors.  For India’s 2019 general election, the company launched several tools to combat misinformation. Suspicious articles were shown lower in newsfeeds and page administrators were alerted if they shared debunked articles. A “candidate connect” tool also gave users verified information on local candidates.

Set.3- With the prime minister and chief ministers meeting to develop a plan of action to tackle the surge in Covid-19 cases, it is critical that the Supreme Court does its bit to enable the executive to focus on the job at hand. The court must direct high courts and lower courts to transfer all Covid-related cases to it, and encourage them not to entertain cases that prima facie appear to transgress into the executive’s domain. The danger posed by the pandemic is far from over. Central and state governments must not be encumbered by demands, some of which appear to be frivolous in nature. The judiciary, on its part, must restrict its observations to points of law. The Delhi High Court’s observations on the use(A)/ and alleviation of vaccines, the decision to provide vaccines(B)/to countries as grant assistance, and maintaining control on the levels(C)/ of export, are clear instances of the court going beyond i ts jurisdiction(D). The courts can ask GoI for clarification and explanation, but asking vaccine manufacturers Bharat Biotech and Serum Institute of India to provide details about their production capacity and inventory is literally not their business, but only serves to add confusion. The roll-out of the biggest vaccination drive to date is a massive logistical exercise. It is also a critical one, as central and state governments have to ensure a steady pace of vaccination to safeguard against new strains and resurgence of Covid-19. At the same time, GoI has to ensure that vaccine production keeps pace with demand, and that the country is meeting its various export obligations. GoI needs to make it clear that one of the driving forces behind its vaccine grant programme is understanding that no country is immune till the world is. So, ensuring vaccine availability in low-income and low-middle-income countries and in our neighbourhood is in enlightened self-interest. Beating Covid-19 requires all stakeholders to work together in common purpose. Efforts to divert attention and confuse do no one any good. Instead, it dangerously detracts from the common goal of tackling the pandemic.