Look through the words scattered around this page. Every one of them is among the most commonly used words in the English language.
They come from a 2023 list of about 2,800 words, shown to cover over 90% of general English use, intended for people learning the language.
This 2023 list is an update of an earlier one, made in 1953, which identified about 2,300 words as the essential vocabulary to everyday life at the time.
Between the two lists, 70 years apart, about 600 words were dropped, and over 1,100 were added. The rest remained as is.
Some of the changes make immediate sense: Telegraph dropped out; computer was added, along with website and blog. Tobacco was replaced by cigarette. Motherhood became mom, and dad was added too, though fatherhood was never on the list to begin with. The world changed and vocabulary surely followed.
But also: apple didn’t make the new list. Neither did fork, soap, umbrella or leaf, for example. It’s not that these things vanished from everyday life, but many hands-on words became less central to the core vocabulary. Dog stayed; goat and donkey didn’t. Bread stayed; breadmaking ingredients—flour and wheat—dropped. Cook is on the new list. Boil, bake, and fry are not.
And many of the words that were added, such as mortgage, corporation, appropriate, analysis, fairly, and despite, don’t look anything like the ones that were discarded. In fact, they are mostly abstract concepts that don’t look like anything at all.
How the Words We Teach English Language Learners Changed, and What That Says About Us
These “essential vocabulary” lists are called the General Service List (1953) and the New General Service List (2013, revised in 2023).
They were designed as teaching tools for people learning English as a second language, built from real-world usage data and extensively tested. The aim was a vocabulary list with as few words and as much coverage of everyday English usage. That coverage is high, over 90% for the 2023 list1 and about 84% for the 1953 list.2 To account for that much of the language, they had to track a significant portion of whatever people were actually reading and saying. A word earned its place by appearing often enough, across enough contexts, to be hard to avoid for the average person in an English-speaking society. Open the word lists panel on the right to browse through all the entries in both lists.
While these were practical tools, built to capture which words people need most, the answer also doubles as a snapshot of ordinary life, 70 years apart: what people were expected to engage with, and had to deal with, in their daily lives.
Treating the lists as an indirect record of day-to-day life, I went through the differences between them from a few angles: what the words were about, how tangible were they, and to which parts of speech they belonged.
The Expanding World
I started by using a common linguistics research tool3 that sorted all of the words by meaning. It assigned each word to one of 21 subject categories, based on typical usage: Food and Farming, the Body and the Self, Government and Public, Language and Communication, and so on. Together, they suggested what kind of world each list was built for.
The New List Devotes More Space to Abstract Concepts, and Less to the Physical World.
Each band is one of 21 semantic categories, sized and sorted by its share of each list.
Data source: all words run through the UCREL Semantic Analysis System (USAS).
The categories that shrank are mostly those that have to do with the immediate, physical world, while the gains are those furthest from it.
To better see this, the categories can be oriented spatially. Some categories describe you: your body and emotions. Some describe what’s immediately around you: food, objects, and the natural world. Others name systems you participate in: government, institutions, society, and culture. And some have no location at all: abstract concepts, reasoning, and processes. When we look at the data grouped by physical scope, the pattern of change seems to point in a specific direction.
The Vocabulary Moved Outward
The 21 semantic categories from earlier, now grouped by their scope: the self, the immediate world, institutions, social life and communication, and abstract terms.
Data source: all words run through the UCREL Semantic Analysis System (USAS), then grouped into five umbrella-term domains. Expand to view the full category breakdown.
- The Self: Emotion | The Body and the Individual
- Local/Immediate: Substances, Materials, Objects and Equipment | Food and Farming | Life and Living Things | Architecture, Housing and the Home | World and Environment
- Institutional: Money and Commerce in Industry | Government and Public | Education | Science and Technology
- Social/Communicative: Social Actions, States, and Processes | Movement, Location, Travel and Transport | Language and Communication | Entertainment, Sports and Games | Arts and Crafts
- Universal/Abstract: General and Abstract Terms | Psychological Actions, States and Processes | Numbers and Measurement | Names and Grammar | Time
In hindsight, the shift makes sense. By 1957, four years after the original list was published, white-collar workers outnumbered blue-collar for the first time in US history. And by 2000, fewer than one in four workers did manual labor. The stuff people encountered in their daily lives, what they needed to talk about, and the systems they had to navigate all changed.
The vocabulary lists, built from the language of their respective eras, tracked those changes. The shifts reflect a life that moved further from its own making: less tied to tools, animals, food, and the body; more tied to national or global institutions, categories, systems, and ideas.
The new vocabulary—mortgage, legislation, perspective, involvement, improvement, assumption, evaluation—are words you can’t weigh, point to, or hold in your hand. These words shape your life, but they do it without occupying physical space.
Harder to Picture
To better understand whether there was a shift in vocabulary describing the physical world, I compared each word to a database that rates its tangibility on a scale of 1 to 5 (called a “concreteness rating4”). A rating of 5 means you can experience the word directly with your senses, while a rating of 1 means you can’t.
More Abstract Words, Fewer Concrete Ones
Concreteness ratings of both lists, from abstract (1) to concrete (5).
Kernel density estimation, bandwidth 0.08 · Data source: Brysbaert et al. (2014)
This shift matters because abstract and concrete words are processed by our brains in different ways. When you read axe, your brain doesn’t just decode letters, it reaches for something: an image, a weight, or a gesture. The word activates both a verbal label and a sensory trace. Psychologists call this dual coding:5 Concrete words travel through two channels, verbal and sensory; abstract words travel through one. Two channels mean two retrieval pathways, which is why concrete words are “stickier,” easier to hold in a line of thought and faster to recall. Abstract words, on the other hand, are purely verbal, and have to be understood through language alone.
To put it another way: Concrete words are easier for us to process because they are bundled with a web of associations, tactile experiences, and memories that anchor their meaning. Here’s a more detailed view of the shift away from concrete language:
The Concrete End Hollowed Out. Something Murkier Filled In.
Data source: Brysbaert Concreteness ratings for 40 thousand generally known English word lemmas. The dataset provided 99.8% coverage of the words in both lists. 6 words not in the dataset are not included in this chart: as, dialog, english, gaiety, madden, old-fashioned.
While concrete words have sensory grounding to carry their meaning, abstract words rely on other parts of speech to specify, soften, or sharpen what they mean. That help tends to come from one particular corner of the language: adverbs.
How Much, How Often, How Certain
Nouns Still Dominate Both Lists, Verbs Remained Steady, and Adjectives Grew Modestly. Adverbs, However, Nearly Doubled.
Each square is one word, grouped by part-of-speech in each list. Hover the cells to see the words.
The 2023 list contains more words overall (2,809 vs. 2,284). All changes mentioned in the text reflect each category's share of its list, not raw counts. Data source: NLTK (Natural Language Toolkit), with manual correction of mislabeled words.
Axe doesn’t need an adverb to modify it; you know what it is. But acceptable, relevant, and adequate come with conditions, qualifications, and degrees that need to be spelled out. Adverbs do precisely that: language to calibrate language.
Look through all the adverbs that were added:
Most of the adverbs specify degree, frequency, certainty, and extent. Some hedge (somewhat, partly, relatively, possibly, approximately). Others assert (absolutely, definitely, entirely, exactly, precisely). They're all doing the same kind of work: Take a statement and tell you how much of it is true, how often, and how certain. It’s as if the world now requires you to be more precise about everything.
Further
Bread survived both lists. Flour, wheat, harvest and bake didn’t. The word for what sustains us remained essential, while the words for how we’d make it weren’t. That might be the most honest summary of what happened.
The world that made the 2023 list is more regulated, more connected, and in many ways more capable than the one behind the 1953 list. It’s a world further than our kitchen or home, reaching across economies, institutions, and democracies.
Today's vocabulary reflects a life that is less self-contained and more systemic. It’s less about what’s within arm’s reach, and more about the larger world we navigate through. That sort of long-distance connection requires a particular kind of language: expansive, abstract, and precise. And language, it turns out, can’t help itself. It keeps track.
Methods & Notes
I compared two prominent vocabulary lists for English learners: the General Service List (GSL, 1953; 2,284 words) and the New General Service List (NGSL 1.2, 2023; 2,809 words). I labeled words appearing on both lists as “remained” (1,656), words only on the 1953 list as “removed” (628), and words only on the 2023 list as “added” (1,153).
The GSL words came from the Simple English Wiktionary GSL. The NGSL words came from the official NGSL 1.2 file (“alphabetized and lemmatized for research”). The NGSL uses lemmas (one entry per word family); the GSL sometimes lists inflected forms as separate headwords. These lists track word forms deemed worth teaching based on frequency and usefulness, not abstract concepts. For example, the word being is on the GSL as its own headword and was not included in the NGSL, But this doesn’t mean the concept of existence left the language. In the NGSL it falls under be, which is on both lists.
Why treat the lists as a portrait of everyday English?
Both lists were built for teaching, but external research suggests each covers a large share of everyday language use. About 84% of general English for the GSL and about 90% for the NGSL, depending on the text and how words are counted. I did not re-run those corpus analyses myself. I take the published materials as given and rely on coverage figures from the list authors and from follow-up studies (including an independent check on American English by Stoeckel, 2019 – see footnotes). That’s why the differences between the lists felt worth examining as more than a curriculum update, with the caveat that neither list is a neutral census of culture.
Where can I find the data?
All tagged words: remained, removed, and added, with semantic tags, concreteness ratings, and part-of-speech labels are in this public spreadsheet. You can also browse the word lists in the word-list panel on the right side of this page.
How did I sort words by meaning?
Each word was tagged with the UCREL Semantic Analysis System (USAS), using the 21 top-level categories. USAS also assigns much finer sub-categories (there are hundreds), but I stayed at the top level so the charts could show broad shifts without splitting the words into overly granular bins.
I chose not to correct mislabels. For example, hammer, nail, and wax are all tagged “General and Abstract Terms”, but in USAS’s finer tags, they read as actions (“to hammer,” “to nail,” “to wax”), not objects. Out of context, many of these words go multiple ways, and it didn’t feel right to override that case by case; USAS is an established linguistic framework, and swapping in my own judgment would mix two different standards.
For the second chart, I grouped USAS’s 21 categories into five “scope” domains (self, local, institutional, social, abstract). That grouping is my editorial choice, not part of USAS. It came from noticing a spatial quality to the trends seen across the 21 categories.
How did I measure concreteness?
Concreteness ratings come from Brysbaert et al. (2014). I used these as-is. Six words weren’t in the database and were left out of the concreteness charts: as, dialog, english, gaiety, madden, and old-fashioned.
How did I tag parts of speech?
Parts of speech were tagged with NLTK, simplified to five categories. Here I did intervene, but only when a word was clearly mislabeled (132 words, 3.8% of the list; mostly adjectives mislabeled as nouns). When a word can act as more than one part of speech depending on context, I left the tag as-is and deferred to NLTK as the established framework, using the primary, most common label. Here I also used an LLM strictly to help flag potential errors in NLTK’s output.
What are the limitations?
Both lists rank words by frequency, then apply learner-focused curation. Michael West’s 1953 list especially reflects period pedagogy. He favored general-purpose vocabulary over emotional or highly specific words, not just whatever appeared most often (Therova, 2020, summarizing West, 1953, pp. ix–x). Some of what looks like “1950s life” may also be how mid-century ESL teaching filtered the language. I still treat the lists as a portrait of everyday English because both cover a large share of running text and speech that goes well beyond the classroom.
Footnotes
- On NGSL’s ~90% coverage: Browne, Culligan & Phillips, NGSL project. See also: A New General Service List: The Better Mousetrap We’ve Been Looking for?, Browne (2014); and An Examination of the New General Service List, Stoeckel (2019). ⏎
- On GSL’s ~84% coverage: A general service list of English words with semantic frequencies, West (1953); The New General Service List: A core vocabulary for EFL students and teachers, Cambridge ELT (2018). ⏎
- UCREL: Semantic Analysis System (USAS). ⏎
- Concreteness ratings for 40 thousand generally known English word lemmas, Brysbaert, M., Warriner, A. B., & Kuperman, V. (2014). Behavior Research Methods, 46, 904–911. ⏎
- Why are pictures easier to recall than words? Paivio, A., Rogers, T.B. & Smythe, P.C. Psychon Sci 11, 137–138 (1968). ⏎