心无鸿鹄志 怎知不可耀四方——玛雅·安吉罗
In 1945, two sculptures
1945年 两座代表着
meant to represent the average man and woman in the United States
标准美国男人和女人的雕塑
went on exhibit at the American Museum of Natural History.
在美国自然历史博物馆展出
Based on measurements taken from tens of thousands of young men and women,
它们是人们基于对成百上千年轻男女的测量
they were called Norma and Norman.
雕刻而成 被命名为诺玛和诺曼
That same year, a contest launched to find a living embodiment of Norma.
同年 还举办了一场寻找真人版诺玛的比赛
“Normal” is often used as a synonym for “typical” “expected”
“正常”一词常用作“模范”“期望”
or even “correct”.
甚至“正确”的代名词
By that logic,
按照这个逻辑
most people should fit the description of “normal”.
大多数人都应符合“正常”的定义
And yet, not one of almost four thousand women who participated in the contest
然而 在参赛的近四千名女性中没有一名
matched Norma, the supposedly normal woman.
能与诺玛 这个所谓的正常女性相匹配
This puzzle isn’t unique to Norma and Norman, either.
这样费解的事并不只在诺玛和诺曼身上发生
Time and time again, so-called normal descriptions
一次又一次的结果显示 我们对自己身体 思维
of our bodies, minds, and perceptions,
和感知方面的所谓正常的定义
have turned out to match almost no one.
几乎与任何人都不匹配
And yet, a lot of the world is constructed
然而 世界上很多事物都是
around a foundation of normalcy.
围绕着正常标准构建的
So what does normal actually mean?
那么正常的含义到底是什么？
And should we be relying on it so much?
我们是否应当如此依赖于它呢？
In statistics, a normal distribution describes a set of values
在统计学中 正态分布是指一组
that fall along a bell curve.
落在一条钟形曲线上的数值
The average or mean, of all the values is at the very center,
所有数值的平均值位于最中心
and most other values fall within the hump of the bell.
其他数值大多落在靠近平均数的两边
These curves can be tall,
钟型曲线可能很高
with most values inside a narrow range,
多数数值都在一个狭窄范围内
or long and flat,
也可能分布的很宽
with only a slight bias towards the average.
数值都与平均值相差无几
What makes the distribution normal,
正态分布之所以能表示正常标准
is that it follows this curved shape.
是因为它符合钟型曲线的形状
Normal doesn’t describe a single data point,
正态指的不是单一的数据点
but a pattern of diversity.
而是多元化的模式
Many human traits, like height, follow a normal distribution.
人类的许多特征都符合正态分布 比如身高
Some people are very tall or very short,
有一部分人特别高或特别矮
but most people fall close to the overall average.
但大多数人还是趋近总体平均值
Outside of statistics, normal often refers to an average
抛开统计学来说 正常标准一般是指一个平均值
like the single number pulled from the fattest part of the bell curve,
比如从钟型曲线最厚的一部分中抽出一个数值
that eliminates all the nuance of the normal distribution.
会抹去正态分布中所有的细微差别
Norma and Norman’s proportions came from such averages.
诺玛和诺曼的参数比例就取自这样的平均值
Applied to individuals, whether someone is considered normal
就个体来说 一个人是否被视为正常
usually depends on how closely they heel to this average.
通常取决于他与这个平均值的接近程度
At best, such definitions of normal
最好的情况下 这种对正常标准的定义
fail to capture variation.
也没法描述个体差异
But oftentimes, our calculations of normal are even more flawed.
但很多时候我们对正常值的计算 常存在更多缺陷
Take the BMI-or Body Mass Index.
拿BMI 身体质量指数来说
BMI is a measure of weight relative to height,
BMI是体重与身高的衡量指数
with different ratios falling into “underweight”
根据不同的比率 划分为“体重过轻”
“normal weight” “overweight” and “obese” ranges.
“体重正常”“过重”和“肥胖”
Generally, only BMIs that correspond to normal weight
通常 只有BMI指数处于正常体重的人
are considered healthy,
才被视为身体健康
but BMI is not always an accurate predictor of health,
但BMI并不总是与健康状况
or even of what’s a healthy weight.
甚至健康体重相关的准确指标
BMI doesn’t take into account body fat percentage,
BMI没有考虑到体脂率
body fat distribution,
身体脂肪的分布
levels of physical activity, or blood pressure.
运动量 或血压
And yet, those who fall outside the so-called normal range
然而 体质指数在所谓正常范围以外的人
are commonly advised that losing or gaining weight will improve their health.
通常会被建议减重或增重来改善健康状况
When we apply a standard of normal to all of humanity
正常标准的数据来源于一个无代表性的数据部分
that’s based on data from a non-representative slice,
当我们把它适用于全人类时
we’re not just choosing one point on the distribution,
并不是从分布中选取一个数据点
we’re choosing it from the wrong distribution.
而是选择了错误的分布
A lot of behavior science research draws from samples that are pretty WEIRD,
许多行为学研究的样本都很奇怪
meaning Western, educated,
都是西方的 受过教育的
industrialized, rich and democratic.
现代工业化的 富有的 和民主主义的人
These features can skew norms
即使研究与这些样本没有显著的联系
even in research that doesn’t have an obvious link to them.
在关联的研究中 它们也会使标准出现偏差
Take the famed Muller-Lyer optical illusion:
以著名的Muller-Lyer视错觉为例：
it’s normal to think one of the two lines is longer,
人们普遍认为图上两条线中有一条更长
when they’re actually the same length,
但实际上两条一样长
at least, if you’re an American undergraduate.
至少如果你是个美国本科生 就会这么想
A team of anthropologists and psychologists
一组人类学家与心理学家发现有一群人
found other demographic groups were much less susceptible,
不太容易受到该错觉的影响
members of the San people of the Kalahari
像卡拉哈里的桑人族群
weren’t susceptible to the illusion at all.
就完全不会被影响
When these limited or inaccurate definitions of normal
当这些狭义的 或不正确的定义
are used to make decisions that impact people’s lives,
被用来做决策 影响人们的生活时
they can do real harm.
真的很要命
Historically, such concepts of normal
在历史上 这样的正常概念
have been hugely influential.
曾产生重大影响
The Eugenics Movement of the early 20th century
20世纪初的优生运动
weaponized the concept of normal,
将正常的概念武器化
using it to justify exclusion, violence
来为排斥 暴力压制
and even extermination of those deemed not normal.
甚至灭绝那些被认为不正常的人辩护
To this day, people are often targeted and discriminated against
时至今日 还有人因为残疾 精神问题
on the basis of disabilities, mental health issues,
性取向 性别认同 以及所有
sexual orientations,
被定义为“不正常”的
gender identities, and other features deemed “not normal”.
问题受到针对和歧视
But the reality is that the differences in our bodies, minds,
但事实上 我们的身体 思想 感知
perceptions, and ideas about the world around us,
还有对周围世界的观念都不尽相同
in short, diversity is the true normal.
简而言之 多元化才是真正的正常
And speaking of deeply flawed systems of measurement,
说到存在严重缺陷的检测体系
how much do you know about the dark history of IQ tests?
你对智商测试的黑历史了解多少呢？
Learn more with this video,
观看本期视频了解更多
or get the latest and unimportant to be,
或关注最新且无关紧要的讨论
should we get rid of standardized testing?
我们应该取消标准化考试吗？