Which of the following best explains the phrase "Such warnings do not amount to arguments against globalisation" in the context of the passage ? ?->(Show Answer!)

1. Which of the following best explains the phrase "Such warnings do not amount to arguments against globalisation" in the context of the passage ?

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MCQ-> Read the following passage and answer the given questions. After the Second World War, the leaders of the Western world tried to build institutions to prevent the conflicts of the preceding decades from recurring. They wanted to foster both prosperity and interdependence, to 'make war not only unthinkable but materially impossible'. Their work bore fruit. Expanded global trade has raised incomes around the world. While globalisation is sometimes portrayed as a corporate plot against the workers; that was not how it was seen before 1914. British trade unions were in favour of free trade, which kept down food prices for their members and also opened up markets for the factories in which they worked. Yet, as the Brexit vote demonstrates globalisation now seems to be receding. Most economists have been blindsided by the backslash. Free trade can be a hard sell politically. The political economy of trade is treacherous. Its benefits, though substantial, are dilute, but its costs are often concentrated. This gives those affected a strong incentive to push for protectionism. Globalisation itself thus seems to create forces that erode political support for integration. Deeper economic integration required harmonisation of laws and regulations across countries. Differences in rules on employment contracts or product safety requirements, for instance, act as barriers to trade. Trade agreements like the TransPacific Partnership focus more on "nontariff barriers" than they do on tariff reduction. The net impact of this is likely to be that some individuals, consumers and businesses are not likely to be as benefitted as others and given rise to discontent. Thus the consequences of such trade agreements often run counter to popular preferences. Joseph Stiglitz, a Nobel Prize winner, has warned that companies influence over trade rules harms workers and erodes support for trade liberalisation. Clumsy government efforts to compensate workers hurt by globalisation contributed to the global financial crisis, by facilitating excessive household borrowing, among other things. Researchers have also documented how the cost of America's growing trade with China has fallen disproportionately on certain American cities. Such costs perpetuate a cycle of globalisation. Periods of global integration and technological progress generate rising inequality, which inevitably triggers two countervailing forces, one beneficial and one harmful. On the one hand, governments tend to respond to rising inequality by increasing redistribution and investing in education, on the other, inequality leads to political upheaval and war. The first great era of globalisation, which ended in 1914, gave way to a long period of declining inequality, in which harmful forces played a bigger rise than beneficial ones. History might repeat itself, he warns. Such warnings do not amount to arguments against globalisation. As many economists are quick to note, the benefits of openness are massive. It is increasingly clear, however, that supporters of economic integration underestimated the risks both that big slices of society would feel left behind and that nationalism would continue to provide an alluring alternative. Either error alone might have undercut support for globalisation and the relative peace and prosperity it has brought in combination, they threaten to reverse it.What can be concluded from the example of Britain cited in the passage ?
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MCQ->Which of the following best explains the phrase "Such warnings do not amount to arguments against globalisation" in the context of the passage ?....

MCQ-> Read the passage carefully and answer the given questionsThe complexity of modern problems often precludes any one person from fully understanding them. Factors contributing to rising obesity levels, for example, include transportation systems and infrastructure, media, convenience foods, changing social norms, human biology and psychological factors. . . . The multidimensional or layered character of complex problems also undermines the principle of meritocracy: the idea that the ‘best person’ should be hired. There is no best person. When putting together an oncological research team, a biotech company such as Gilead or Genentech would not construct a multiple-choice test and hire the top scorers, or hire people whose resumes score highest according to some performance criteria. Instead, they would seek diversity. They would build a team of people who bring diverse knowledge bases, tools and analytic skills. . . .Believers in a meritocracy might grant that teams ought to be diverse but then argue that meritocratic principles should apply within each category. Thus the team should consist of the ‘best’ mathematicians, the ‘best’ oncologists, and the ‘best’ biostatisticians from within the pool. That position suffers from a similar flaw. Even with a knowledge domain, no test or criteria applied to individuals will produce the best team. Each of these domains possesses such depth and breadth, that no test can exist. Consider the field of neuroscience. Upwards of 50,000 papers were published last year covering various techniques, domains of enquiry and levels of analysis, ranging from molecules and synapses up through networks of neurons. Given that complexity, any attempt to rank a collection of neuroscientists from best to worst, as if they were competitors in the 50-metre butterfly, must fail. What could be true is that given a specific task and the composition of a particular team, one scientist would be more likely to contribute than another. Optimal hiring depends on context. Optimal teams will be diverse.Evidence for this claim can be seen in the way that papers and patents that combine diverse ideas tend to rank as high-impact. It can also be found in the structure of the so-called random decision forest, a state-of-the-art machine-learning algorithm. Random forests consist of ensembles of decision trees. If classifying pictures, each tree makes a vote: is that a picture of a fox or a dog? A weighted majority rules. Random forests can serve many ends. They can identify bank fraud and diseases, recommend ceiling fans and predict online dating behaviour. When building a forest, you do not select the best trees as they tend to make similar classifications. You want diversity. Programmers achieve that diversity by training each tree on different data, a technique known as bagging. They also boost the forest ‘cognitively’ by training trees on the hardest cases - those that the current forest gets wrong. This ensures even more diversity and accurate forests.Yet the fallacy of meritocracy persists. Corporations, non-profits, governments, universities and even preschools test, score and hire the ‘best’. This all but guarantees not creating the best team. Ranking people by common criteria produces homogeneity. . . . That’s not likely to lead to breakthroughs.Which of the following conditions, if true, would invalidate the passage’s main argument?
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MCQ-> Read the following passage carefully and answer the questions given below it. Certain words/phrases have been printed in bold to help you locate them while answering some of the questions. The wisdom of learning from failure is incontrovertible. Yet organisations that do it well are extraordinarily rare. This gap is not due to a lack of commitment to learning. Managers in the vast majority of enterprises that I have studied over the past 20 years —pharmaceutical. financial services, product design, telecommunications, and construction companies: hospitals; and NASA’s space shuttle program, among others— genuinely wanted to help their organisations learn from failures to improve future performance. In some cases they and their teams had devoted many hours to afteraction reviews, postmortems, and the like. But time after time I saw that these painstaking efforts led to no real change. The reason: Those managers were thinking about failure the wrong way. Most executives I’ve talked to believe that failure is bad (of course!). They also believe that learning from it is pretty straightforward: Ask people to reflect on what they did wrong and exhort them to avoid similar mistakes in the future—or, better yet, assign a team to review and write a report on what happened and then distribute it throughout the organisation. These widely held beliefs are misguided. First, failure is not always bad. In organisational life it is sometimes bad, sometimes inevitable, and sometimes even good. Second, learning from organisational failures is anything but straightforward. The attitudes and activities required to effectively detect and analyze failures are in short supply in most companies, and the need for context-specific learning strategies is underappreciated. Or – ganisations need new and better ways to go beyond lessons that are superficial (“Procedures weren’t followed”) or self-serving (“The market just wasn’t ready for our great new product”). That means jettisoning old cultural beliefs and stereotypical notions of success and embracing failure’s lessons. Leaders can begin by understanding how the blame game gets in the way. The Blame Game Failure and fault are virtually inseparable in most households. organisations, and cultures. Every child learns at some point that admitting failure means taking the blame. That is why so few organisations have shifted to a culture of psychological safety in which the rewards of learning from failure can be fully realised. Executives I’ve interviewed in organisations as different as hospitals and investment banks admit to being torn: How can they respond constructively to failures without giving rise to an anything-goes attitude? If people aren’t blamed for failures, what will ensure that they try as hard as possible to do their best work? This concern is based on a false dichotomy. In actuality, a culture that makes it safe to admit and report on failure can—and in some organisational contexts must–coexist with high standards for performance. To understand why, look at the exhibit “A Spectrum of Reasons for Failure,” which lists causes ranging from deliberate deviation to thoughtful experimentation. Which of these causes involve blameworthy actions? Deliberate deviance, first on the list, obviously warrants blame. But inattention might not. If it results from a lack of effort, perhaps it’s blameworthy. But if it results from fatigue near the end of an overly long shift, the manager who assigned the shift is more at fault than the employee. As we go down the list, it gets more and more difficult to find blameworthy acts. In fact, a failure resulting from thoughtful experimentation that generates valuable information may actually be praiseworthy. When I ask executives to consider this spectrum and then to estimate how many of the failures in their organisations are truly blameworthy, their answers are usually in single digits—perhaps 2% to 5%. But when I ask how many are treated as blameworthy, they say (after a pause or a laugh) 70% to 90%. The unfortunate consequence is that many failures go unreported and their lessons are lost. Question : sophisticated understanding of failure’s causes and contexts will help to avoid the blame game and institute an effective strategy for learning from failure. Although an infinite number of things can go wrong in organisations, mistakes fall into three broad categories: preventable, complexity-related, and intelligent.Which of the following statement (s) is/are true in the context of the given passage ? I. Most executives believe that failure is bad and learning from it is pretty straightforward. II. The wisdom of learning from failure is disputable. III. Deliberate deviance, first on the list of the exhibit, “A Spectrum of Reasons for Failure” obviously warrants blame.....