[0] https://xcancel.com/AlexGDimakis/status/2002848594953732521
In the canonical example, you have uncorrelated attributes, eg skill and attractiveness in actors, forming a round scatter plot with no correlation. Selecting a subpopulation of top actors who are either skilled or attractive, you get a negative correlation. You can visualize this as chopping the top-right of the round scatter plot off: the chopped off piece is oriented in roughly a line of negative correlation.
In this example, if you look in the linked paper inside the post by Dimakis, there is a positively correlated scatter plot: You can tell the shape is correlated positively between youth and adult performance. But in this case, if you condition on the extremes of performance, you end up selecting a cloud of points that has flat to slight negative correlation.