MoAR: so that you can get some work done, today ..

.. i've narrowed down this week's roundup to only a few shared posts, this week. enjoy!

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i can't tell if it's the same graph as before ..

.. but there's bad news for STEM ph.d's out there. when they said that they want more graduates working in science and engineering, maybe they meant only undergraduate degrees?

"Jordan Weissmann, an editor at The Atlantic, analyzed the latest NSF figures. Upon graduation, he says, "Ph.D.s in general have a less than 50 percent chance of having a full-time job, and that percentage has been decreasing for about 20 years."

Worse yet, as of 2011, approximately one-third of people graduating with a doctoral degree in science, technology, math or engineering had no job or post-doctoral offer of any kind."

~ from "Are There Too Many Ph.D.s And Not Enough Jobs?" @npr

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a controversial issue: gender in maths, worldwide.

well, 1.5 million data points sound like a lot. so provided they accounted for the usual national, societal, and social factors (e.g. percentage of girls that have access to primary education), i'd say that the result is rather striking.

"We did not find a sex difference in mathematics among the lowest performing students, but this is where the sex difference in reading was largest. In contrast, the sex difference in mathematics was largest among the higher performing students, and this is where the sex difference in reading was smallest. The implication is that if policy makers decide that changes in these sex differences are desired, different approaches will be needed to achieve this for reading and mathematics. Interventions that focus on high-achieving girls in mathematics and on low achieving boys in reading are likely to yield the strongest educational benefits."

~ from "Sex Differences in Mathematics and Reading Achievement Are Inversely Related .." @plos-1

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two different kinds of advice.

the first bit of advice is about .. well, advising.  (it reminds me of the mind-set of grant writing, actually.)

"A project that is going to take eight years of construction work before it produces any scientific results cannot and should not be built by a PhD student. On the other hand, a project that dries up in two years is equally bad. In other words, no matter what idea I come up with, I need to be able to say that all the candidates I hire should find enough material to write a thesis and graduate—no matter what the experimental outcome.

This means that any big idea I come up with also needs to be partitioned into chunks of the right size. If it can't, then it doesn't work in an academic institution. Since all experimental results need to be thesis-worthy, the questions I want to answer should be open enough to accommodate failure. For instance, my ideas are often based on a single experiment: if we conduct experiment "a," we could measure property "b," and that would be so cool! But, what if "a" doesn't work? Does the student go home?"

~ from "From idea to science: Knowing when you’ve got a good idea" @arstechnica

the next bit of advice is about writing .. or more precisely, rules about storytelling. here are two:

"8. Finish your story, let go even if it’s not perfect. In an ideal world you have both, but move on. Do better next time.

9. When you’re stuck, make a list of what WOULDN’T happen next. Lots of times the material to get you unstuck will show up."

~ from "Pixar’s 22 Rules of Storytelling" @aerogrammestudio

i like to think of #8 as "just submit the damned paper!" and #9 as 'it never hurts to try building counter-examples' .. (-:

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lastly, another thousand words.

~ from "Inside Wonderland" by Jaume Plensa