Is there a name for this sort of logical fallacy?

[Ferguson97]

When people assume that because instance of X is higher among Y group, then Y group must suffer from that instance of X at a higher rate -- when in actuality, instances of X could be uniform across alln groups, but members of Y group are just more likely to report instances of X?

Another more specific example would be: suppose a university implements a new program designed to tackle sexual assault on campus. Prior to the implementation of this program, approximately 10% of the student body reports an instance of sexual assault. Following the implementation of this program, approximately 20% of the student body reports an instance of sexual assault.

A person looks at that and assumes "oh no! the program backfired and increased the number of sexual assaults!" when in reality, it's just making people more likely to be willing to report instances of this.

Sort of like that chart showing the increase in left-handedness over time. People aren't actually becoming more left-handed over time, it's just that the stigma basically doesn't exist anymore.

Is there a specific name for this?

[Antonio V]

Yep: https://en.wikipedia.org/wiki/Reporting_bias

It's called a bias, not a fallacy, because it's not per se a logical error, but merely a data interpretation error.

[Torie]

Also in play is the shy voter, where the respondent knows it is not respectable to hold a given opinion, or to be unaware of something, so they lie, or deflect.

What percentage of voters in NY-03 would admit that they voted for Santos?

[Biden his time]

On a similar note, it also probably is a fallacy when people interpret data in a certain way that they assume performances among different groups of people are because of reporting bias (without further evidence to back this up) and not taking the data at face value.

I wonder if that has a name?

[Associate Justice PiT]

On a similar note, it also probably is a fallacy when people interpret data in a certain way that they assume performances among different groups of people are because of reporting bias (without further evidence to back this up) and not taking the data at face value.

I wonder if that has a name?

     Could be considered a type of Secundum Quid, since the heart of that error is confusing rules with exceptions. Whether it is the Accident or Converse Accident type depends on your guess as to how common reporting bias really is.