Kevin Knight is the Blog and Social Media Editor of the National Catholic Register.
“History is mostly guessing; the rest is prejudice.” —Will Durant
How do you count — or miscount — the crowd at a pro-life march? Taking the Jan. 13 Celebrate Life March in Denver as an example, let us count the ways.
Method #1 — How to Count a Stationary Crowd
There's a science to this, but it's not rocket science. It's just a matter of multiplying area times density.
Area estimation is the easy part thanks to drones, digital maps and other tools. In the Google Earth image below, the shaded half-circle on the lawn roughly matches the perimeter of the crowd at Denver’s Celebrate Life March:
Google Earth’s polygon tool gives an area of about 30,000 square feet for this shape, so let’s start with that.
Density is a little trickier, but there are some solid rules of thumb to help. As Popular Mechanics explains, a man named Herbert Jacobs came up with this rule: “a light crowd has one person per 10 square feet, a dense crowd has one person per 4.5 square feet, and... mosh-pit density would have one person per 2.5 square feet.”
So multiplying area times density, there might have been between 3,000 and 6,000 people at this event on Saturday.
Method #2 — How to Count a Moving Crowd
After the Denver crowd rallied at the Colorado state capitol, they marched through the heart of the city. Here’s a video clip:
It's always tougher to count a crowd when it’s moving, but this video is helpful. The four-minute clip captures about half of the march, which took about eight minutes to pass. Assuming that 300 people walked by each minute, that's a crowd size of 2,400 people. (If you come up with a different count after watching the video, feel free to post that in the comments below.)
Method #3 — How to Count a Pro-Life Crowd
Then there’s the “make up a random number” method, which was used by a local news station after the March. Granted, it’s a lot quicker than the rarely-used “count ears and divide by two” method, but it doesn't seem to be quite as accurate: