One about killed a woman by not identifying her pregnancy is ectopic. Many anti abortion folks are convinced that even ectopic pregnancies can be viable.
These places promise things like free pregnancy tests and medical advice to get people in the door.
They really just exist to pressure women into not getting abortions. They will lie through their teeth - all the classics, like suggesting that an abortion makes it impossible to get pregnant again, or that abortion causes cancer - they’ll say anything to prevent an abortion.
They are pretty much completely unregulated, and present themselves as secular non profits.
Well in Gilead, wouldn’t a woman need permission to have sex?
Have you seen the latest louis theraux docu about the manospere? They literally say that. More than 40% of young males think these people make positive messages.
Doesn’t everyone need permission to have sex? From the person they’re having sex with, no doubt…
Who else could they be claiming someone would need permission from?
and 90% of statistics are made up
I’m a data analyst. A significant part of any statistic is selecting the dataset to aggregate over, which often means filtering it down to the subset you’re interested in, and responsible analysis has to be aware of the bias that introduces.
Suppose you’re tracking delivery times. If I calculate the average time from order to delivery for orders placed in the last week, none of the orders will have a delivery time greater than one week. I’ve had to argue why we should use the orders delivered last week instead.
On the other hand, if a set of orders is delayed, we won’t immediately see that spike in turnaround time until they actually get delivered, so we need to separately track and compare the amount of open orders and their respective age at the start of the week to put the turnaround time in context.
The problem I see with many statistics online, particularly ones just reposted somewhere else as summary, is intransparency about the criteria for selecting and aggregating the data, the impact of context and the bias resulting from both.
Every statistic is skewed in some way, but without explaining how and why, it’s easy to misunderstand (or even misrepresent) them.
In essence: 90% of statistics are worthless. Even if not made up, they might as well be.
(That one definitely is made up though.)