The reason is just as you've stated, there are many different ways to define "gay". I don't think 3-5%+ numbers have been "wrongly" tossed around, except to the extent that you disagree with how the being "gay" is defined. The higher estimates, anywhere between 5 and 10% are life-time prevalence numbers, not snapshots at a point in time.
Are you gay if you identify as gay?
Are you gay if you have same-sex attractions which you may have never acted on?
Are you gay if you have had sex with someone of the same sex EVER, or only if you have done so recently?
When you are estimating the "gay" population, are you using the life-time prevalence, or only the prevalence at this point in time?
At what age are you asked to identify your behavior/attractions? If a 13 year old virgin is asked if he's had gay sex, and he's said no because he's a virgin, does that make him straight or could he still be gay?
I would not say any single definition is wrong, it just has to be understood for what it is. Even among reputable & professional studies, there is no standard definition used. IMO, the "correct" definition largely depends on the purpose of the study.
For example, the Center for Disease Control & Prevention uses "Has engaged in same-sex activities in the last 5 years for men over the age of 13, regardless of sexual identity or attraction". And this definition makes sense for those who are concerned strictly about the spread of STD's around those who engage in same-sex sexual behavior. But a substantial number of minors 13-18 have not had sex, and will thus be excluded from the that statistic. Consequently, psychologists and those who want to understand the extent and nature of problems that gay youth face would likely use a different definition.... either identity, or same-sex attraction, regardless of if they've had sex or not. There are practical reasons for using one definition vs another, but I agree that these statistics are often misused and misrepresented, mostly by those who don't understand the difference between the statistics that aren't actually measuring the same thing.


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