For a long time I've wondered how to measure nonconformity. To measure nonconformity I needed to define "nonconformity". But no matter how I defined "nonconformity" my definitions felt so subjective they could apply to anybody, from a certain point of view. If everybody is nonconformist then nobody is nonconformist because the word "nonconformist" isn't meaningful.
Today I realized that the opposite of conformity is audacity.
audacity
noun, plural au·dac·i·ties.
boldness or daring, especially with confident or arrogant disregard for personal safety, conventional thought, or other restrictions.
effrontery or insolence; shameless boldness: His questioner's audacity shocked the lecturer.
Usually audacities . audacious or particularly bold or daring acts or statements.
Audacity is bold, daring, shameless and impertinent. Cultivate these qualities and you will cultivate nonconformity.
My favorite technique of boldness is to simply tell the truth. One trick is to never prefix statements with "I believe". Don't say "I believe ". If is true then just say "". (If is untrue then don't say and don't believe .) The unqualified statement is bolder. Crocker's rules encode boldness into a social norm.
Daring comes from doing things that scare you.
Shamelessness comes from not caring what other people think on short time horizons.
The most impressive people I know care a lot about what people think, even people whose opinions they really shouldn’t value (a surprising numbers of them do something like keeping a folder of screenshots of tweets from haters). But what makes them unusual is that they generally care about other people’s opinions on a very long time horizon—as long as the history books get it right, they take some pride in letting the newspapers get it wrong.
―The Strength of Being Misunderstood by Sam Altman
Impertinence comes from treating superiors as equals. I don't know how to cultivate impertinence because I'm status-blind to begin with. Impertinence is the opposite of submission; it is dangerous to be impertinent when your livelihood is on the line.
I think this is a fairly big mistake.
First, as a practical matter, one does not actually need to define something in order to measure it; often, the process works in the reverse order. For instance, I would guess that early scientists trying to measure temperature or air pressure first made a measurement device, then defined "temperature" or "air pressure" as the thing they measured. (Or if they did try to define temperature/air pressure beforehand, their definitions were probably incomplete/wrong until after they had the measurement devices.)
Second, and more importantly: when someone wants to "define" a word, they are usually confused about how words work. Definitions, as we usually use them, are not the correct data structure for word-meaning. Words point to clusters in thing-space; definitions try to carve up those clusters with something like cutting-planes. That's an unreliable and very lossy way to represent clusters, and can't handle edge-cases well or ambiguous cases at all.
If you want to measure some abstract thing like "nonconformity", then I'd suggest a process more like this:
Note that you may not find one big factor which intuitively seems to match "nonconformity"! Whether "nonconformity" is a useful, predictive abstraction at all is an empirical question.
(Side note: I jumped from talking-about-clusters to talking-about-factor-analysis. Mathematically, these both do a very similar thing, at least if we're talking about Bayesian clustering models: both try to find some relatively-low-dimensional latent variables such that our observables are conditionally independent given the latents.)
Alternatively, rather than a formal factor analysis, you could use the intuitive equivalent: take a bunch of "proxy measures" or even just a list of examples, and try to intuit the unifying, shared aspect which makes them all good proxies/examples. This can be "less noisy" than a formal factor analysis, since you have some intuition for which-parts-are-important. This is especially useful for coming up with good mathematical definitions.