Why should I trust the data?

There have been too many times of selective definitions, selective measurements, selective polling, selective measurements... all for reaching an agreed upon conclusion. For example, the CDC used a specific definition of rape (excluding forced penetration, counting it as general sexual assault instead) that excluded the majority of male victims of domestic rape, and then used the now biased results to give high level summary data that was greatly misleading.

If I can't trust the CDC's reporting on an issues as serious as domestic sexual violence, then how can I trust anyone's data? Maybe peer reviewed science in the hard sciences, but social science (including economics) has a similar issue of selective measurements, ignored replication, and biased publishing.

So I guess to start with, what peer review has this undergone? To what extent has it been replicated? What criticisms does it have (and none is a very bad sign)? What is the biases of the group(s) that did the work involved? What is the biases of the group(s) that provided funding?

Yes, it is odd I'm at the point where anecdotes seem to have as much weight as data because anecdotes are understood to be inherently biased whereas data is treated as pure, reliable, and free of bias when it isn't.

Also, please note that someone has already posted a criticism of this data.