具体描述
“Range is an urgent and important book, an essential read for bosses, parents, coaches, and anyone who cares about improving performance.” —Daniel H. Pink
What's the most effective path to success in any domain? It's not what you think.
Plenty of experts argue that anyone who wants to develop a skill, play an instrument, or lead their field should start early, focus intensely, and rack up as many hours of deliberate practice as possible. If you dabble or delay, you’ll never catch up to the people who got a head start. But a closer look at research on the world’s top performers, from professional athletes to Nobel laureates, shows that early specialization is the exception, not the rule.
David Epstein examined the world’s most successful athletes, artists, musicians, inventors, forecasters and scientists. He discovered that in most fields—especially those that are complex and unpredictable—generalists, not specialists, are primed to excel. Generalists often find their path late, and they juggle many interests rather than focusing on one. They’re also more creative, more agile, and able to make connections their more specialized peers can’t see.
Provocative, rigorous, and engrossing, Range makes a compelling case for actively cultivating inefficiency. Failing a test is the best way to learn. Frequent quitters end up with the most fulfilling careers. The most impactful inventors cross domains rather than deepening their knowledge in a single area. As experts silo themselves further while computers master more of the skills once reserved for highly focused humans, people who think broadly and embrace diverse experiences and perspectives will increasingly thrive.
用户评价
##用 pss.plus 读完。例子篇幅太长。
评分##Outliers的作者做了首页推荐，其实两本书的观点并不矛盾，综合起来看，个人成长应尽可能拓展知识宽度和经历的丰富性（range)，找到真正的兴趣点和专长之后再集中精力出成就，先前探索的过程也不会被浪费，有range的成就反而可能会更大。只给三颗星是因为作者很多观点挺好，但论证过程太多例子看着重复且累
评分##剖析了很多大家习以为常的理论，提供了不同的见解。
评分##3.5
评分##Outliers的作者做了首页推荐，其实两本书的观点并不矛盾，综合起来看，个人成长应尽可能拓展知识宽度和经历的丰富性（range)，找到真正的兴趣点和专长之后再集中精力出成就，先前探索的过程也不会被浪费，有range的成就反而可能会更大。只给三颗星是因为作者很多观点挺好，但论证过程太多例子看着重复且累
评分##剖析了很多大家习以为常的理论，提供了不同的见解。
评分##“想要相信 或者 我已经相信了” 这样是不对的，这本书大量引用Khaneman，不如直接去读Khaneman，现阶段对我无appeal | 大致略读 文中材料不新（10yr+）例子局限 作者本身是个reportor不是科学家
评分##Point taken but 一篇文章可以搞定的事 写一本书完全没必要
评分近1年商业/社科最佳。给了非常多案例讨论了：10000h什么时候是不必要的（late-specialization），是否应该转专业/转行（match quality+个人成长），什么时候data-driven的文化是有害的，不同问题/领域（类比思维+问题结构分析）如何移植经验，都很有启发. 最重要的是给了希望转变、没有很早确定目标的人信心 —— don't feel behind. 遗憾的是没有给specialization更多的讨论，e.g. 在什么时候specialize是必要的，什么时候generalize是好的，这样整个话题会更全面、客观
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