HackerURLs

一次又一次被重新发现的经典。

同一个链接,相隔一年以上,一次又一次被人重新发现、再次冲上 Hacker News 首页。能经受住这种时间检验的,大多是值得一读再读的文章。每篇附中文标题,讨论最热的那些再加上中文导读和高赞评论翻译。

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上首页次数最多、而且有中文导读的 30 篇。时间轴上每个黑点是一次上首页,空心点是一次没冲上去的投稿。

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经典库

按第一次上首页的年份分布,点柱子筛选。

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    这些经典是怎么挑出来的

    1. 01

      合并同一个链接

      读取 Hacker News 自 2006 年以来的全部链接投稿,把 http/https、www、跟踪参数等写法不同的同一篇文章合并成一条。

    2. 02

      只留经得起时间的

      同一链接至少两次拿到 50 分以上(约等于上首页),而且两次相隔一年以上;再由 AI 剔除状态页、产品首页和新闻事件。

    3. 03

      写导读、译评论

      上首页次数最多的 2,000 篇配上中文导读、"为什么经久不衰",并精选翻译 HN 高赞评论。导读由 AI 生成,可能有误。

    思考与写作danluu.com

    达克效应及其他迷因

    Dunning-Kruger and other memes (2015)

    3次上首页
    2年跨度
    488累计得分
    249条评论

    2015 — 2017,它一次次回到首页

    黑点是上首页(≥ 50 分)的那次投稿,空心点是没冲上去的投稿,点越大分数越高。

    导读

    作者 Dan Luu 重读邓宁-克鲁格效应等流行心理学结论的原始论文,指出大众流行版本(如“越无知越自信”)与原始研究实际数据存在偏差,并顺带讨论了静态类型、收入与幸福感等话题。文章的核心主张是:很多广为流传的“科学结论”其实是被简化或曲解的迷因。

    为什么经久不衰:它示范了“回到原始文献”这一高回报的求真习惯,提醒读者警惕被简化传播的流行科学叙事,多年来反复引发讨论。

    关键词 邓宁-克鲁格效应原始文献流行科学统计误读

    HN 评论精选

    读原始文献是回报极高的习惯,二手解读常被曲解。

    这篇文章触及了我近年来收益最高的习惯之一:去读原始文献。我不断从中受益——通常会发现下游的解读误解了某些方面、只抓住了故事的一小部分,或者通过臆测缺失的数据、插入符合私人议程的叙事来蓄意歪曲原意。

    ternaryoperator查看英文原文

    This article touches on one of the highest-payback practices I've developed over the last few years: going to the original sources. I am constantly rewarded by this; typically finding out that the downstream analysis misunderstood some aspect, latched on to only a fraction of the whole story, or willfully misrepresented by speculating on absent data or by inserting a plausible narrative for items that fit a private agenda.

    澄清了 D-K 效应的真正含义:低能力者高估自己,但并非认为自己比高手更强。

    我不明白他想就邓宁-克鲁格效应表达什么观点。我听过的唯一流行版本是:最差的人往往高估自己,最好的人往往低估自己,展示的数据似乎确实支持这一解读。(后补充)读了另一篇文章后我明白了:常见的误解是以为最差的人会认为自己和最好的人一样强,但研究实际说的是最差的人高估了自己,只是其自我评估仍低于能力更高者的自我评估。

    krig查看英文原文

    I don't understand what point he is trying to make about the Dunning-Kruger effect. The only pop-sci version of the study that I've heard is that the bottom percentile tends to overestimate their abilities while the top percentile tends to underestimate their abilities. The data shown certainly seems to support this interpretation? edit: I read the article linked in another comment below [1] and now I think I understand what claim the original article was referring to. It seems a common misunderstanding of the D-K effect is that the bottom percentile would think that they are as competent or more competent as the top percentile. However, this is not what the study says, the bottom percentile is overestimating their ability but the estimations are still relatively lower than the self-estimations of those with higher ability. [1]: http://www.talyarkoni.org/blog/2010/07/07/what-the-dunning-kruger-effect-is-and-isnt/

    流行表述虽夸张,但原始研究确实显示低能力者严重高估自己。

    “一个人对某主题了解越少,就越觉得自己懂”这一说法是夸张,多数人也明白它是夸张。但原始研究清楚表明:能力不足的人对自身能力有严重高估——在全部四个实验中,实际能力处于 10% 的人自评为 50-70%。这与 Urban Dictionary 的通俗定义完全一致。

    jpatokal查看英文原文

    "The less someone knows about a subject, the more they think they know." I think that's an exaggeration and understood by most people to be one. What is, however, absolutely clear from the original study is that incompetent people have a highly inflated assessment on their own abilities: in all four experiments (!), the people with actual 10% abilities rated themselves at 50-70%. This is perfectly in line with eg. Urban Dictionary's definition[1]: "A phenomenon where people with little knowledge or skill think they know more or have more skill than they do." http://www.urbandictionary.com/define.php?term=Dunning-Kruger%20effect [1] Chosen intentionally because this is a "popular" source, not an academic one.

    批评作者树立了稻草人,他引用的数据反而支持大众版本。

    作者只是自认为他对邓宁-克鲁格的理解高于常人。正如其他人指出的,这个迷因并不是说实际能力与自我评估负相关,而是说无知的人不知道自己有多无知——即处于低端的人高估了自己相对于最高水平的位置。作者引用的图表其实很好地支持了这一版本。

    notacoward查看英文原文

    The author only thinks his understanding of Dunning-Kruger is better than average. No, seriously. As others have pointed out, the meme is not that actual ability and self-assessment are negatively correlated. It's just that ignorant people don't know how ignorant they are - i.e. that those at the low end of the scale overestimate their position relative to the maximum. That version is very well supported by the graphs the OP cites. He has scratched the iceberg of skepticism and now thinks he's enough of an expert to tell the rest of us that we're Doing It Wrong.

    历次讨论

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