Estimating and judging a person is a fundamental necessity for any human. Is a person reliable? Is she kind? Is he depressed and requires help?
Humans make these judgments both consciously and unconsciously all the time. But are we good at it?
Advances in behavioral sciences have often shown how unrationally humans think and process information. An inventory of potential biases or information processing lapses are needed to be better at making judgements. One such potential processing lapse is perhaps not heeding to what one can call variance of character. (maybe there’s an existing technical term for this 🤷)
Take two people, A and B.
A and B are, if you can hypothetically average out every single trait of a human, very similar (see graph). However, it could often be the case (no real study was conducted on this by the author whatsoever) that they are estimated to be quite different as individuals.
This could be because one person, in this case A, is much prone to character swings (a much broader version of mood swings encompassing every single character trait a human can have) — perhaps, on one day he’s an open social animal and on the other he can barely get himself to talk. Maybe he openly likes a ‘cringe’ piece of music because he feels secure but on his more insecure days he joins the mob in mocking those who like the same piece of music. Regardless, on most days he is like B, who is stable and is consistently in the middle of both extremes. In that case, one can say that A has a higher character variance than B.
Consequently the accuracy with which a person, say C, can delineate A and B as people (given C has symmetrical, i.e., exact number and type of interactions with both A and B) is contingent on four broad factors:
- Total number of interactions — how many times.
- Quality of interactions—how much of each persons individual self do they bring out.
- Diversity of interactions — how diverse are the socio, economic, spatial, linguistic, temporal factors.
- Perceptiveness of C — how competent is C at noticing character and processing it.
The higher each individual factor is, the more accurate one can judge A and B — assuming that with each new data point we approach closer to the mean. So C might conclude that A and B are polar opposites if C only met each of them twice. Only when C meets them both, say, 30 times can he realise how, in fact, A and B are quite similar. Of course, if the difference in character variance is much higher between the two folks, it would take much more than 30 interactions to figure it out.
So what does all of this boil down to? Don’t solidify judgements too quickly.
Note: Graph only for representational purposes.