This will come as no surprise to folks who attempt to follow climate science through the media, but a recent study really sheds some interesting light on how the media report science based on their pre-conceived notions, and not on the science itself.  Alex Tabarrok discusses media reporting on the relative math skills of men and women.  The politically correct view is that there are no differences, so it seems that was going to be the way the new science was reported, whether the data matched or not:

For the past week or so the newspapers have been trumpeting a new study
showing no difference in average math ability between males and
females.  Few people who have looked at the data thought that there
were big differences in average ability but many media reports also
said that the study showed no differences in high ability.

The LA Times, for example, wrote:

The study also undermined the assumption — infamously espoused by
former Harvard University President Lawrence H. Summers in 2005 — that
boys are more likely than girls to be math geniuses.

Scientific American said:

So the team checked out the most gifted children. Again, no difference.
From any angle, girls measured up to boys. Still, there’s a lack of
women in the highest levels of professional math, engineering and
physics. Some have said that’s because of an innate difference in math
ability. But the new research shows that that explanation just doesn’t
add up.

The Chronicle of Higher Education said:

The research team also studied if there were gender discrepancies at
the highest levels of mathematical ability and how well boys and girls
resolved complex problems. Again they found no significant differences.

All of these reports and many more like them are false.  In fact, consistent with many earlier studies
(JSTOR), what this study found was that the ratio of male to female
variance in ability was positive and significant, in other words we can
expect that there will be more math geniuses and more dullards, among
males than among females.  I quote from the study (VR is variance
ratio):

Greater male variance is indicated by VR > 1.0. All VRs, by state and grade, are >1.0 [range 1.11 to 1.21].

Notice
that the greater male variance is observable in the earliest data,
grade 2.  (In addition, higher male VRS have been noted for over a
century).  Now the study authors clearly wanted to downplay this
finding so they wrote things like "our analyses show greater male
variability, although the discrepancy in variances is not large."
Which is true in some sense but the point is that small differences in
variance can make for big differences in outcome at the top.  The
authors acknowledge this with the following:

If a
particular specialty required mathematical skills at the 99th
percentile, and the gender ratio is 2.0, we would expect 67% men in the
occupation and 33% women. Yet today, for example, Ph.D. programs in
engineering average only about 15% women.

Both the WSJ and economist Mark Perry get it right.