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Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Ages Survey: Results, published by jefftk on June 5, 2023 on LessWrong.
A few weeks ago after the
community meeting with the Department of Children and Families I decided to run a survey to learn more about the range of ages at which people generally thought kids might be ready to do various activities without supervision. Stay home for a few hours? Play at the park alone? Take public transit? I put something together on
Google Forms and shared it
on
Facebook and over email. Several friends shared it further, and over the next two weeks it gathered 219 responses. In reading the following please remember that this is not a representative sample of anything: it's heavily oversampling people geographically and socially similar to me!
The main part of the survey was a series of questions about scenarios
("play in an unfenced backyard", "cross a medium-traffic street", "spend the night home alone") and asking "what age you'd guess the typical child in your area could learn to do it without supervision". Here are the average responses:
The survey also asked "the ages you'd guess for an especially mature child (90th percentile) or an especially immature child (10th percentile)", assuming "the child doesn't have any relevant disabilities." Here's that chart again, with the addition of the estimates for especially mature or immature children:
Taking medians is helpful for distilling each question down to a few numbers, but the wide range of responses are interesting. Here are CDF plots for each question. The way to read these is that at a given age (x-axis) they tell you what fraction of parents (y-axis) think a child this old is likely ready. You can think of the previous bar chart as a collection of the the y=50% slices from each of the charts below:
I'm also interested in how people's backgrounds relate to their answers in these scenarios. First, let's look at what demographics we saw. The median respondent was 40 when they filled out the survey:
Most respondents were female (83%), followed by male (13%), and non-binary (5%).
Living in an urban area, most of the people I was able to survey also lived in an urban area:
They overwhelmingly grew up in more suburban areas, though:
Most respondents were parents (88%) and the most common number of children was 2 (45%):
The median parent's oldest child was 8 and most of the parents had an oldest child under 18 (92%), but there were a few parents of grown children:
So, how do these demographics interact with what sorts of ages people gave? Here is how the respondents differed from the mean, in years. For example, a dot at +1y indicates that this respondent on average gave answers one year larger than others. We can see that women generally gave ~1y higher ages than men, with non-binary respondents in between:
The orange bar is median, green triangle is mean.
Normally you'd use z-scores for this, where the x-axis is "standard deviations away from the mean" but in this case the standard deviations are similar between questions and I think it easier to think about with the x-units in years. This does mean that questions with more variance effectively have a bit more weight in determining how to classify each respondent.
Here's the same chart, but by respondent ages:
Ignoring the four responses from kids because of the small sample size, it looks like older people generally gave higher ages. I don't know if this is because they're farther from having kids in the relevant age ranges, have become more conservative over time, or were drawn from a somewhat different population than the younger people in the sample? If we ran this survey decades ago I'd expect to generally see younger ages, so this is a counter-intuitive result!
Here's by location:
It looks like people who live in exurban or rural areas, generally gave higher ages. This is...
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