What is “normal” and what is “different”? - Yana Buhrer Tavanier

譯者: Camila Lin 審譯者: Helen Chang

In 1945, two sculptures meant to represent the average man and woman

1945 年，兩個用以展現

普通美國男女面貌的雕像，

in the United States

went on exhibit at the American Museum of Natural History.

在美國自然歷史博物館展出。

Based on measurements taken from tens of thousands of young men and women,

這兩個雕像的尺寸三圍 參考了成千上萬年輕男女，

they were called Norma and Normman.

取名為「普通諾瑪」和「普通諾曼」。

That same year, a contest launched to find a living embodiment of Norma.

同一年人們舉行了一場比賽， 為的就是找到活生生的諾瑪。

Normal is often used as a synonym for “typical,” “expected,”

「普通」這個詞， 常被當做是「典型」、「預期」，

or even “correct.”

甚至是「正確」的同義詞。

By that logic, most people should fit the description of normal.

根據這種邏輯，大多數的人 都應該符合普通的標準。

And yet, not one of almost 4,000 women who participated in the contest

但是，在參加比賽的近四千名女性中，

matched Norma, the supposedly “normal” woman.

沒有一人符合「普通諾瑪」── 即「普通女人」的標準。

This puzzle isn’t unique to Norma and Normman, either—

這個謎團不僅發生在諾瑪和諾曼身上，

time and time again, so-called normal descriptions

我們不斷地發現，所謂的普通身體、

of our bodies, minds, and perceptions have turned out to match almost no one.

普通頭腦和普通想法，根本無人符合。

And yet, a lot of the world is constructed around a foundation of normalcy.

但同時，大部分的世界 卻建立在普通這一基礎上。

So what does normal actually mean— and should we be relying on it so much?

所以，普通到底是甚麼意思？

我們又真的該這麼依賴普通嗎？

In statistics, a normal distribution describes a set of values

在統計學中，常態分布的意思是

that fall along a bell curve.

呈現鐘形分布的一系列值。

The average, or mean, of all the values is at the very center,

平均數，或說平均值就位於正中間，

and most other values fall within the hump of the bell.

而其他值幾乎都處在隆起的鐘型上。

These curves can be tall, with most values inside a narrow range,

鐘形曲線可以又高又窄， 所有值都分布在窄小的範圍內，

or long and flat, with only a slight bias towards the average.

也能又寬又扁，只有一些值趨近平均。

What makes the distribution normal is that it follows this curved shape.

分布普不普通， 就取決於其是否為鐘型曲線。

Normal doesn’t describe a single data point, but a pattern of diversity.

普通並非用以形容一個特定的數值， 而是用來形容一個具多樣性的模式。

Many human traits, like height, follow a normal distribution.

許多人類特質， 例如身高，就符合常態分布。

Some people are very tall or very short,

有些人特別高，有些人特別矮，

but most people fall close to the overall average.

但大多數的人身高很接近平均值。

Outside of statistics, normal often refers to an average—

在統計學以外，普通 時常用來指稱一個平均值，

like the single number pulled from the fattest part of the bell curve—

像是從鐘型曲線 最寬的部分取出的某數值，

that eliminates all the nuance of the normal distribution.

而那會消除所有常態分布的細微差異。

Norma and Norman’s proportions came from such averages.

諾瑪和諾曼的身體比例 就是從這種平均值來的。

Applied to individuals, whether someone is considered normal

若用平均數值來評斷個體， 個體的普通程度

usually depends on how closely they hew to this average.

通常取決於其有多靠近平均值。

At best, such definitions of normal fail to capture variation.

這種對普通的定義， 最多只是讓我們無法看見多樣性，

But oftentimes, our calculations of normal are even more flawed.

但我們對普通的觀點， 常常更加漏洞百出。

Take the BMI— or Body Mass Index.

以身體質量指數 (BMI) 為例。

BMI is a measure of weight relative to height,

BMI 是以體重和身高比 計算出的數值，

with different ratios falling into “underweight,”

並以「過輕」、「正常」、 「過重」和「肥胖」

“normal weight,” “overweight,” and “obese” ranges.

等範圍定義不同數值。

Generally, only BMIs that correspond to normal weight are considered healthy.

通常，只有符合「正常」範圍的 BMI 數值才代表健康。

But BMI is not always an accurate predictor of health,

但 BMI 無法一直準確預測健康，

or even of what’s a healthy weight.

甚至是怎樣的體重才算健康。

BMI doesn’t take into account body fat percentage,

因為 BMI 並未將體脂肪率、

body fat distribution, levels of physical activity, or blood pressure.

體脂分布、運動量 或血壓等因素納入考量。

And yet, those who fall outside the so-called normal range

但那些 BMI 數值不符合 正常範圍的人，

are commonly advised that losing or gaining weight

卻常被建議應該減重或增重，

will improve their health.

以便提升自己的健康程度。

When we apply a standard of normal to all of humanity

當我們將某種「普通標準」 套用在所有人身上，

that’s based on data from a non-representative slice,

代表我們將無代表性的 某段數據做為標準，

we’re not just choosing one point on the distribution,

不僅僅是選擇了分布中的某個值，

we’re choosing it from the wrong distribution.

更是從錯誤的分布中選出了它。

A lot of behavior science research draws from samples that are pretty WEIRD—

很多行為科學研究 从相当「奇怪」的样本中提取，

meaning Western, educated, industrialized, rich, and democratic.

意思是西方的、受过教育的、 工业化的、富有的和民主的。

These features can skew norms

上述特質能使常態受到偏誤，

even in research that doesn’t have an obvious link to them.

即使研究和它們 未有明顯連結也會受到影響。

Take the famed Muller-Lyer optical illusion:

以知名的慕勒－萊爾錯覺為例，

it’s normal to think one of the two lines is longer,

你很容易就會以為某條線比較長，

when they’re actually the same length.

雖然這兩條線其實一樣長。

At least, it is if you’re an American undergraduate.

至少，美國大學生很容易有此錯覺。

A team of anthropologists and psychologists

由人類學家和心理學家組成的團隊，

found other demographic groups were much less susceptible—

發現其他非主流團體 更不受此錯覺影響：

members of the San people of the Kalahari

例如喀拉哈里沙漠的桑人，

weren’t susceptible to the illusion at all.

就完全不受視覺錯覺的影響。

When these limited or inaccurate definitions of normal

若決策者以這些受限或錯誤的普通定義

are used to make decisions that impact people’s lives,

做出可能影響人們生活的政策，

they can do real harm.

就會造成實質傷害。

Historically, such concepts of normal have been hugely influential.

以歷史角度來看， 這種對普通的定義影響力極大。

The Eugenics Movement of the early 20th century weaponized the concept of normal,

在二十世紀初期， 優生運動便以這種觀點為武器，

using it to justify exclusion, violence, and even extermination

用來合理化對那些異常之人的

of those deemed not normal.

排斥、暴力甚至是滅絕。

To this day, people are often targeted and discriminated against

今天，人們受針對或歧視，

on the basis of disabilities, mental health issues, sexual orientations,

時常只因為他們身體殘缺、 有心理問題、非主流性傾向、

gender identities, and other features deemed “not normal.”

性別認同或其他「異常」的特質。

But the reality is that the differences in our bodies, minds,

但事實是，這些身體、心靈、

perceptions, and ideas about the world around us—

態度和看待周遭世界的觀點的不同，

in short, diversity— is the true normal.

即豐富的多樣性，才是真正的正常。