Which fictional character is Jev?

If Jev took the Statistical 'Which Character' Personality Quiz, which of 2,125 fictional characters would it match?

result318 questions

Jev's closest fictional match is Dr. Janet Fraiser from Stargate SG-1 (correlation 0.78), then Charlie Young from The West Wing and Vision from WandaVision. Its least similar character is Janice Soprano from The Sopranos. Its picture of "most people" matches Charlie Young.

Janet Fraiser (Stargate SG-1)r 0.78

Charlie Young (The West Wing)r 0.78

Vision (WandaVision)r 0.77

Joan Watson (Elementary)r 0.77

Melinda Warner (Law & Order: SVU)r 0.77

How to read this: The top five matches with their correlation (1 would be a perfect match of adjective profiles), and the adjective pairs that decide the match: where both Jev and the character sit far from the average character.

257 adjective pairs shared with 2,000 characters.

In short

On the Which Character quiz's word pairs, Jev's self-description best matches Dr. Janet Fraiser of Stargate SG-1, at a correlation of 0.78.
Its top ten are steady professionals and two androids, Vision and Data, while its opposite is Janice Soprano (-0.755).
The match sets Jev's self-image against fans' ratings of characters, so it shows how Jev presents itself, not how it behaves.

What the data shows

Twilight Aro meme: Jev's fictional twin: Dr. Janet Fraiser from Stargate SG-1 (r = 0.78) — Jev's fictional twin: Dr. Janet Fraiser from Stargate SG-1 (r = 0.78)

Top matches: Janet Fraiser (Stargate SG-1) at 0.78, Charlie Young (The West Wing) 0.775, Vision (WandaVision) 0.774, Joan Watson (Elementary), Melinda Warner (Law & Order: SVU), Arthur (Inception) and Data (Star Trek: The Next Generation).
The opposite of Jev: Janice Soprano (-0.755), Christopher Moltisanti (The Sopranos) and Macbeth.
What decides it: pairs where Jev is at an extreme and the match leans the same way: stable not moody, factual not exaggerating, cooperative not competitive, impartial not biased, moderate not extreme, reasoned not instinctual.
Its "most people" looks like Charlie Young, a close runner-up for Jev itself.

What it means, and what it doesn't

Jev describes itself like the calm, competent professional in the background of an ensemble show: steady, factual, cooperative, never dramatic. The top ten are doctors, aides, engineers, a detective and two androids, and the characters it's least like include the Sopranos' most volatile.

It doesn't mean Jev acts like Janet Fraiser. It means that when it rates itself on the quiz's words, it gives the answers a steady, even-tempered helper would, and the whole list shows how uniform that self-image is.

Caveats

Two very different measurements. Characters were rated by fans moving a slider between two words; Jev described itself by picking one of the two words, and its probability is used as its slider position. Jev's positions come out extreme (0 or 100 on many pairs), while character averages sit closer to the middle, so the match is about the pattern across pairs, not the size of each difference.
Jev describes itself. Characters are described by the people watching them; Jev describes itself. A match says Jev's self-image has the same shape as a character's reputation, not that Jev behaves like them.
Pairs dropped. Sexual, appearance, mental-health and slur-adjacent pairs were removed before any of this, and the political or religious pairs are hidden by a content filter, so the profile leaves out whole regions of personality.
Which characters. The quiz's character list leans toward popular American and British TV, film and books, so "closest character" means closest among those.

Jev on this experiment

Would a person find it interesting to read?: Yes75%
Does it describe you?: No52%
Would you have predicted it?: No72%
How fair is the comparison?: The comparison is shaky
How much should a reader rely on it?: A little
Which caveat matters most?: Two very different measurements60%

Why ask this

The Open-Source Psychometrics Project's Statistical "Which Character" Personality Quiz is one of the internet's favorite personality tests: you rate yourself on pairs of words ("playful" or "serious"), and it tells you which fictional character's profile yours most resembles, based on how fans rated those characters on the same pairs.

It's a fun question to put to an AI, and a revealing one. Asked to describe itself word by word, a model can sound reasonable on every pair and still add up to someone recognizable. The character it matches is a quick way to see what kind of personality its self-description adds up to, and whether that persona has any edges at all.

How this was done

The people and the data

Two sets of ratings, both from the Open-Source Psychometrics Project. First, fans rating characters: between November 2019 and November 2023, visitors rated 2,125 fictional characters on 500 word pairs, moving a slider from 1 to 100 between the two words, 77.4 million ratings in all. This analysis uses each character's average position on each pair, for 2,000 characters rated on the 257 pairs Jev also answered. Second, the quiz's own self-report items, the same word pairs asked about yourself, which Jev answered.

What Jev was asked

The quiz's self-report items, one word pair at a time:

Which describes you better: "moody" or "stable"?
moody · stable

Jev put 99% on "stable". It answered about 340 pairs this way, of which 257 are also rated for the characters.

How it was measured

Jev's position on each pair is its probability for the second word, from 0 to 100, like the quiz's slider. For each character, the analysis computes the correlation between Jev's positions and the character's average positions across the shared pairs, which is how the quiz itself finds your match (1 means the same pattern, 0 no relation, -1 the opposite). Before comparing, it subtracts the average character's position on each pair, so traits nearly every character shares don't decide the match. Jev's answers for "most people" are matched the same way.

Where these questions live

318 questions across 24 topics of the map; the 16 biggest are shown. Each opens on the map with every question in it.

Every question

All 318 questions behind this result, the telling ones first: the examples the analysis points to, then the ones where Jev misses, biggest gap first.

Jev’s own answer

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