When you say at around 1:23 that "virtually nobody has access to the population standard deviation," while that might be technically true in some cases, Cohen uses an estimate of pop SD in calculating "d" (pooled sample SD * sqrt of df/N) and R&R provide the equation for that calculation in their article, directly under where they list/discuss the Cohen's d equation (it's labeled "5") and appears on screen in your video. So, it's true that in most cases we probably don't have the actual total population sigma, we don't really need it because Cohen's formula uses a calculated estimate, which he provides the equation for. However, I do agree that Hedges' g is the more preferable effect size to report (for independent groups) and I also agree that many researchers may be actually calculating Hedges' in some cases (or even Glass's delta if they use control group SD) and mislabeling/misreporting it as Cohen's. The primary difference is in the denominator and how it's calculated (which differs for different tests), and I think that's where some researchers make the mistakes that lead to the issue you're highlighting here.
Thanks for another excellent video! I do have to point out that perhaps one of the reasons you got so few responses with the search is that you used "Hedge's g" rather than "Hedges' g" or "Hedges's g" as is more correct (his name was Larry Hedges). I do agree that Cohen's d is used in many instances where Hedges' g should be employed and have made that error myself.
It gets even more complicated. since a lot of people refer to Hedge's g as the unbiased estimator of the effect size, where Cohen's d is multiplied by a correction factor. Even worse, most often, it is not clearly stated which one is really meant and used. Last thing, there are other correction factors available, which might work better than Hedge's correction.
