具體描述
“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.
用戶評價
##講的是通纔和專纔的取捨關係，當前世界的技能格局，以及通纔的技能策略
評分##不必看，很失望。
評分##[有聲書] 標題和副標題多少有點簡單粗暴地點齣“成為通纔”的主題，而且書中的例子全都是能力過人的個人（諾貝爾奬得主體育明星古典音樂名人等等），所以很難說普通人若是把成為專纔的精力和機會花在成為全纔上麵，是否是一個正確的選擇。不過具體到每個章節，有意思的觀點很多，尤其是引用的一些研究。個人收獲比較大的在於：學生評價跟學生之後在該專業的錶現成反比，有效學習必須是“痛苦的”；專業訓練讓學生都太“專”瞭，以至於一些測試解決問題能力的研究發現學生無法高屋建瓴地提煉齣精髓、獲得真正解決問題的能力；專傢會受到自己專業知識的限製；越是背景各異的團隊，越能有創新的可能；創新也可以是有效整閤已有的來解決新問題（這一點我覺得現在RStudio在做的很多很切閤這個描述）。個人覺得“專”放在第一，“通”是錦上添花。
評分近1年商業/社科最佳。給瞭非常多案例討論瞭：10000h什麼時候是不必要的（late-specialization），是否應該轉專業/轉行（match quality+個人成長），什麼時候data-driven的文化是有害的，不同問題/領域（類比思維+問題結構分析）如何移植經驗，都很有啓發. 最重要的是給瞭希望轉變、沒有很早確定目標的人信心 —— don't feel behind. 遺憾的是沒有給specialization更多的討論，e.g. 在什麼時候specialize是必要的，什麼時候generalize是好的，這樣整個話題會更全麵、客觀
評分##3.5
評分##不必看，很失望。
評分##David Epstein
評分近1年商業/社科最佳。給瞭非常多案例討論瞭：10000h什麼時候是不必要的（late-specialization），是否應該轉專業/轉行（match quality+個人成長），什麼時候data-driven的文化是有害的，不同問題/領域（類比思維+問題結構分析）如何移植經驗，都很有啓發. 最重要的是給瞭希望轉變、沒有很早確定目標的人信心 —— don't feel behind. 遺憾的是沒有給specialization更多的討論，e.g. 在什麼時候specialize是必要的，什麼時候generalize是好的，這樣整個話題會更全麵、客觀
評分##Finished 10/12 chapters. A great challenge to 10k hour rule and don't be afraid of falling behind. When match quality isn’t good, quitting is a better way out to seek other options you feel passionate about where grit and perseverance are in the way of ‘quitting’. Van Gogh and self-discovery of rare genetic disease example
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