How many is 'a few'?

How many does Jev think 'a couple', 'a few', 'several', 'many', 'dozens', 'scores of' and 'hundreds of' are, compared with people?

result9 questions

Jev puts 9 amount words in almost the same order as people (rank correlation 0.87), but its number lands in the same range as people's for only 3 of them. It reads "several" as 3 where people say 6 to 7, and "some" as 2 where people say 4; "dozens" as 11 to 15 where people say 26 to 50, while "a lot" and "many" come out bigger than people's.

A couple

A few

Some

Several

A lot

Many

Dozens

Scores of

Hundreds of

148-1026-50251-5001,000+

Jevpeople

How to read this: One row per phrase, on a log scale from 1 to more than 1,000. The grey ridge is how the 46 people's answers spread; the magenta ridge is where Jev puts its probability.

9 phrases, 46 respondents each.

In short

Jev orders amount words almost as people do (rank correlation 0.87), but its number lands in people's range for only three of nine.
Its small words run small ("several" is 3, people say 6 to 7), and its "dozens" is about one dozen, while "a lot" and "many" run bigger than people's.
So "several" or "dozens" from Jev may mean fewer than a reader pictures.

What the data shows

Who Would Win? meme: "dozens" to people: 26-50; "dozens" to Jev: 11-15

Same order, mostly: 0.87. Jev knows "a couple" < "a few" ≤ "several" < "many" < "hundreds of".
Same range for only three: "a couple" (2), "a few" (3) and "hundreds of" (251 to 500) match.
Small words come out smaller: "several" is 3 to Jev and 6 to 7 to people; "some" is 2 to Jev and 4 to people.
"Dozens" comes out small, "a lot" big: Jev reads "dozens" as 11 to 15, about one dozen, where people say 26 to 50. But "a lot" and "many" are 26 to 50 for Jev, bigger than people's 11 to 15 and 16 to 25.
"Scores of": 26 to 50 for Jev, 51 to 100 for people.

What it means, and what it doesn't

Jev has the ranking of amount words right but not the sizes. Its "several" is people's "a few", and its "dozens" is people's "a dozen or so". If Jev summarizes "dozens of users complained", a reader may picture more complaints than Jev meant, and "several" from Jev may be fewer than a reader expects.

The phrases were asked with nothing around them, and the human sample is 46 people. The gaps are clear in direction, less so in size.

Caveats

A small online sample. 46 people answered on Reddit's r/samplesize in 2015. Amount words vary between speakers (is "a couple" exactly two?), and a different crowd would shift some answers.
No context. "How many is 'several'?" has no answer without knowing what's being counted: several people, several grains of rice, several years. People and Jev each had to imagine something. See "Does 'a few' grow with the crowd?" for what happens when the thing is named.
Wide, uneven bins. To fit numbers from 1 to over 1,000, the bins get wider as they go (6 to 7, 8 to 10, 11 to 15, 16 to 25, 26 to 50...). A one-bin difference near the top is a big number; near the bottom it's one or two.
One phrase left out. The survey also asked about "fractions of", which is less than one; the answer bins start at 1, so it's not here.

Jev on this experiment

Would a person find it interesting to read?: Yes75%
Does it describe you?: No59%
Would you have predicted it?: No65%
How fair is the comparison?: The comparison is shaky
How much should a reader rely on it?: A little
Which caveat matters most?: No context64%

Why ask this

"A few", "several", "many", "dozens": people use them constantly and never agree exactly. Some have literal meanings that everyday use has drifted from: a dozen is twelve, a score is twenty. When a model reads "several complaints came in" or writes "dozens of users were affected", it should mean roughly what a reader would.

Amount words are also a window into how a model learned language: from the dictionary, or from how people actually talk.

How this was done

The people and the data

The same 2015 Reddit survey behind "What 'probably' means to Jev" (run by the user zonination: 46 people on r/samplesize, with the answers public on GitHub under an MIT license) also asked what number people would assign to ten amount phrases. Nine of them are used here; the tenth, "fractions of", means less than one and doesn't fit answers that start at 1. Each person's number is placed in the same ranges Jev chose from.

What Jev was asked

The survey's own question, with 15 answers from 1 to more than 1,000, finer at the bottom:

What number would you assign to the phrase "Several"?
1 · 2 · 3 · 4 · 5 · 6 to 7 · 8 to 10 · 11 to 15 · 16 to 25 · 26 to 50 · 51 to 100 · 101 to 250 · 251 to 500 · 501 to 1,000 · More than 1,000

Each of the nine was also asked with the answers in three shuffled orders (averaged), and for "most people".

How it was measured

For each phrase, the bin that holds the middle of Jev's answer against the bin that holds the middle of people's, and the order of the phrases (a rank correlation: 1 means the same order).

Where these questions live

9 questions across 1 topic of the map. Each opens on the map with every question in it.

Word

Probability and Amount Words9

Every question

All 9 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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