The End of the Shared Name: A Century and a Half of Baby-Name Diversity
In 1880 the ten most popular boys’ names covered 44% of all American newborn boys. Today they cover 8%. The same collapse appears in every country whose birth register is deep enough to measure it.
Ask someone to picture a mid-century American classroom and they will imagine several boys called Michael and several girls called Mary. That intuition is correct, and it is measurable. What is less widely appreciated is how completely that world has ended — and that it ended everywhere at once, in countries with entirely unrelated naming cultures and unrelated birth-registration systems.
The American century, in one chart
Scroll the chart sideways to see all of it.
| Year | Boys: top 10 | Boys: top 100 | Boys: distinct names | Girls: top 10 | Girls: top 100 | Girls: distinct names |
|---|---|---|---|---|---|---|
| 1880 | 44.22% | 80.14% | 1,058 | 24.65% | 76.55% | 942 |
| 1900 | 34.22% | 74.65% | 1,506 | 19.48% | 68.03% | 2,223 |
| 1920 | 31.57% | 72.12% | 4,989 | 23.25% | 65.76% | 5,767 |
| 1940 | 33.46% | 75.26% | 3,937 | 23.08% | 66.54% | 5,028 |
| 1960 | 29.08% | 74.34% | 4,598 | 16.96% | 61.75% | 7,332 |
| 1980 | 23.58% | 69.73% | 7,293 | 17.1% | 54.27% | 12,161 |
| 2000 | 13.37% | 55.4% | 12,119 | 10.22% | 42.02% | 17,660 |
| 2020 | 7.86% | 39.65% | 14,060 | 7.89% | 32.55% | 17,527 |
| 2025 | 7.98% | 38.03% | 13,930 | 6.99% | 31.5% | 17,297 |
Two things in that chart are worth separating. The first is the decline itself. The second is that girls’ names were always less concentrated than boys’ names — the girls’ line sits below the boys’ line in almost every year on record, and the gap has never closed. Whatever cultural machinery makes parents willing to pick an unusual name has been acting on girls’ names for longer and more strongly, and it is one of the most stable regularities in the entire dataset.
The same thing happened in six other countries
If this were an artefact of how the SSA collects data, it would not replicate. It replicates. Below is the share of births taken by the ten most popular names of each sex, drawn separately for every national register in our data that publishes a list deep enough to make the calculation meaningful. Each panel is a different country, a different statistics agency, and a different set of names.
Scroll the chart sideways to see all of it.
| Country | Source | Years covered | Top-10 share, first year | Top-10 share, latest year | Names listed, latest year |
|---|---|---|---|---|---|
| Scotland | National Records of Scotland | 1974–2025 | 28.2% | 12.59% | 1,982 |
| Canada (Ontario) | Service Ontario / StatCan | 1917–2024 | 35.72% | 8.78% | 3,515 |
| France | INSEE | 1900–2022 | 43.48% | 10.01% | 12,377 |
| Ireland | Central Statistics Office | 1964–2025 | 44.09% | 11.36% | 2,004 |
| Norway | Statistisk sentralbyra | 1945–2025 | 28.43% | 15.12% | 1,052 |
| New Zealand | Department of Internal Affairs | 1900–2025 | 35.8% | 11.3% | 929 |
The starting levels differ, the slopes differ, and the years covered differ — but the direction does not. No register in our data shows naming becoming more concentrated over any sustained period.
Why this matters for anyone reading a “most popular names” list
A number-one name today is not comparable to a number-one name in 1950, and treating the two as equivalent is the single most common error in popular naming coverage. When the top ten covered a third of all boys, being at number one meant a name a child would share with several classmates. At an eight-per-cent top ten, the number-one name is closer to a mild preference than a norm. The rank is the same; the thing the rank describes is not. That is also why a name can climb the chart while the actual number of babies given it falls.
The same arithmetic is why our own site treats a rank as one signal among several rather than a headline, and why runs at number one have collapsed from decades to single-digit years.
Method, and what this cannot tell you
- What is computed. For every year and sex we sum recorded births, count distinct names, and sum births for the names ranked 1–10 and 1–100. The reported figure is that sum as a percentage of all recorded births for that year and sex. No smoothing, no modelling, no interpolation.
- US records before about 1937 are not a birth register. The Social Security Administration’s name data comes from card applications, so the early years count only people who later applied for a card — which understates births and skews toward people who lived long enough to need one. Figures before 1937 should be read as indicative of relative popularity, not as complete counts.
- The SSA suppresses any name/year cell with fewer than five births, so the true long tail of rare names is larger than any count here can show.
- National registers differ in how deep a list they publish. Where a source reports only its top names, its unlisted tail is missing from the denominator, which inflates a measured concentration figure. Every concentration number here is therefore a conservative floor: the real decline in concentration is at least as steep as shown, not steeper than reality.
- Excluded on purpose. Germany is a shifting panel of city registries rather than one national file, so its yearly totals move for reasons unrelated to naming and it cannot support an over-time series. Finland and Iceland publish living-population counts rather than births. Sources publishing only a top-20 list carry too little tail to measure concentration at all.
- The registry behind these studies covers 28 countries and territories, 26 of them with official statistics-agency or civil-registry data. India and Japan are the two exceptions — neither publishes a national given-name ranking, so their figures come from documented survey and aggregated datasets and are never presented as official. Finland and Iceland publish a living-population register rather than annual births and are excluded from every study in this series.
- Meanings and etymologies elsewhere on this site are partly AI-assisted and labelled as such. Nothing in this study depends on that content — every figure here is a count, a rank or a ratio over registry data.
- Reproducing this. The per-name, per-year, per-country figures behind every number here are available through our free public Baby Name API. If you want the aggregate series as a file, ask.
Ganesh G Kamble, “The End of the Shared Name: A Century and a Half of Baby-Name Diversity,” BabyNameSuggestion.com, 2026. https://babynamesuggestion.com/baby-name-research/baby-name-diversity-since-1880/ — figures computed 2026-08-28 07:56 UTC. Journalists and researchers are welcome to reproduce any figure here with attribution; get in touch for the full per-source provenance or a specific cut of the data.
Other studies in this series
- How fast names travelOn a fixed panel of nine national registers with an equal observation window, the median time for a name to spread from its first country to its fourth fell from 113 years to 7.
- Names that changed genderTwenty-eight American names crossed decisively from boys to girls over 146 years of birth records. Under the same test, none crossed the other way.
- When a spelling overtook its rivalSteven passed Stephen in 1949 and never gave it back. US birth records let us date the exact year one spelling of a name overtook another — something a single name page structurally cannot show.
- Why boys’ names end in NThe share of American boys given a name ending in the letter N rose from 13% in the 1940s to 35% in the 2010s. In the 2020s it fell for the first time in eighty years.
- The biggest one-year jumpsSome names do not climb. They detonate. These are the largest single-year multiplications in 146 years of US birth records — reported without any claim about what caused them.
- Names that came back after a centuryThe folk claim is that a name needs roughly a century out of fashion before it can return. It can be tested: a set of names were common before 1930, effectively disappeared for forty years, and are common again now.
- How long number one lastsIn 146 years of US birth records there have been only 24 runs at number one. The runs are getting shorter, for the same reason behind almost every other finding in this series.
All of these draw on the same normalised registry described on the research index, and the underlying figures are queryable through the free Baby Name API.