PTIn a tech startup, age has rules too
Nobody writes in a handbook what the right age is for each place, but people know. The thesis followed a fully remote software startup founded by young people for about three months and showed where these age norms come from and what they do: they weigh on who gets hired, on the labels people give colleagues, on conflict and on the wish to leave. Explained in 12 screens.
Age norms are expectations the group enforces
"Act your age." The phrase sums up the idea: each place expects a certain behaviour and a certain position at each age. Phrases like these, quoted by the thesis from Barbara Lawrence, show the norm at work:
For the literature the thesis draws on (Gibbs, 1965), every norm has three parts. Tap each one:
Sections 1, 2.6 and 2.7 of the thesis (Gibbs, 1965; Neugarten, 1965; Lawrence, 1996 and 2004).
Few studies have looked at age norms inside companies
The search for "age norms" and "organization" found almost 4,000 documents, most about medicine, psychology or family. After the filters, 21 articles were left. Tap each stage:
Section 2.8, Figure 1 and Tables 2 to 5. The sums across the three databases and the count of the 21 by category are our counts (9 + 4 + 5 + 3 = 21). Layer area is proportional to the number of documents.
The research followed a company that exists only online
The company has no office: people work from several countries over Zoom, Slack and other tools. So the research used netnography, ethnography done in an online setting: observing, talking and reading what the community produces. There were three sources. Choose one:
Sections 3.4 and 4.2, Tables 6 and 7 and Figure 2. The sum of observed sessions is our count. The data were read using Braun and Clarke’s six-phase thematic analysis. The researcher knew the company from the inside, having worked there.
At the company, nearly every department averages 30 years old
The startup was born in 2013, set up by three people aged 20 to 23 who met at college in São Paulo. Today it hires people from all over the world. See the average age in each department, first on the full scale of a working life and then through the magnifier:
Sections 3.5, 4.1, 4.3.2, 4.4.3 and 4.6.1 and Table 8. The youngest hire was 20 and the oldest, 55. The HR data are only reliable from 2022 on. We do not name the company or its products.
The same culture draws some people in and pushes others away
A founder described the culture as young and vibrant
: music at meetings, games, happy hours, slang in the chat. For the thesis, it can facilitate or block age norms. Choose a side:
Not everyone joins in. Two scenes from the observation:
Quiz at the end of the general meeting
72 of 98 people at the meeting took part
Game (Kahoot) at the customer success meeting
14 of 20 took part
Sections 4.3.1, 4.4.1, 4.5.1 and 4.7.1. The thesis does not give the age of those who stayed out of the games; it notes that the extra activities appealed more to younger people, while the meetings drew older ones too.
The age norms began with the founders
At first the founders’ concern was something else: having people that would take us seriously
. So they began hiring people their own age or younger. As Schein, an author the thesis draws on, puts it, founders plant the culture and managers pass it on. Go down the cascade, step by step:
Sections 4.3.3, 4.6 and 4.7.3 and Figure 10. Cascade drawn by us from the thesis’s conclusion. On sanctions: the research found only a positive example, promoting those who fit; it found no clear penalty for breaking the norm.
People there describe younger and older colleagues with ready-made labels
The interviewees did not say they held stereotypes, but their sentences showed it. The thesis gathered some of them in Table 9. Can you tell who each one is about?
| Younger | Older |
|---|
Five of the six pairs in Table 9 and section 4.5.2. The same groups get good and bad labels: younger people are "creative" and "flexible" but "can’t manage"; older people "work harder" and "know how to lead" but are "less fun". The research recorded what people believe; it did not measure whether it is true.
Each department has a preferred age
Nobody put an age range in the job ads. Even so, founders, managers and recruiters said they think about age when choosing. And the reason changes from department to department. Tap a block:
Sections 4.3.2, 4.4.2, 4.4.3 and 4.5.3 and the conclusion. For Sales, the results speak of a preference for older people and the conclusion for younger people who master the technology: we show both views. Some quotes appear without a code because the thesis attributes them to different people in different passages.
There, at 30 you already count as older
Before you look: from what age do you think someone counts as an "older worker" at this company?
I think maybe when I get to 30. Because I don’t want to be annoying to people maybe if they have younger people.E6, on when they might leave
of course in the next five to ten years, I would not fit here anymore. Maybe sooner because they (company) will keep hiring Gen Z.E4
Sections 4.5.2, 4.5.3 and 4.6.1 and Table 6. The "30 or older = older" yardstick is the employees’ own and the company’s. Dots carry no codes and are not in the thesis’s order, so no one can be identified; the count of interviewees above the line is ours.
With no plan for growing older at the company, many see themselves leaving
There is no pension or long-term career plan, and health insurance does not cover dependants. The thesis separates two triggers for wanting to leave:
Figure 4 (staff, chart values; the up-to-25 slice is read from the figure) and Table 12 (leavers). Our calculations: people aged 31 or older were 29% of staff and 36% of leavers (9 of 25). The thesis says older workers leave "slightly more"; the sample for the period is small.
Table 10: the 212 departures since 2018, by HR category. The thesis cannot say how many had to do with age: the most common reason is simply "resigned".
Noticing age norms helps decide whether they make sense
For the author, age norms form without people noticing. Understanding them helps improve the company’s culture, hiring and practices.
For founders and leaders
- Founders’ beliefs become house rules: it pays to look at them early, while the structure is still being formed.
- Benefits and long-term plans weigh on the decision to stay.
For recruiters
- "Culture fit" can hide an age preference. (our reading)
- Noting a candidate’s age in the feedback, as the thesis found, weighs on the choice.
For employees
- Labels such as "younger people can’t manage" and "older people can’t adapt" show up without being noticed.
- Conflict between generations in a team can come from these expectations.
What this research does not say
- Other companies and sectors. It is a single tech startup; the author suggests studying older companies and other sectors. · per the author
- How the norms change over time. A longer study would suit a startup, and the observation was online only. · per the author
- Penalties. The research could not show that people who break the norm are penalized, or whether dismissals had to do with age. · per the author
- An insider’s view. The researcher had worked at the company, which helps understanding and may sway the reading. · our note
- How many think this way. There are 15 interviews, with no count of statements; and some quotes carry different codes in different passages. · our note
Credits
ADEGBESAN, Christiana Adebukola. Exploring organizational age norms in a technology startup. Doctoral thesis (Business Administration) · Universidade Presbiteriana Mackenzie, São Paulo, 2024. Advisor: Prof. Dr. Darcy Mitiko Mori Hanashiro.
Research supported by CAPES (Brazil’s federal agency for graduate education), approved by the ethics committee, with participants’ informed consent. People appear only under the thesis’s codes (F, M and E), without each person’s age, country, department or gender, and the company is not named. This version simplifies the work for a general audience.