I often say to grad students: a reasonable thing to aim for in grad school is ~2-3 essentially complete and posted papers, alongside your JMP. This often looks like your JMP, plus your 2nd-yr paper, a paper from RA'ing for a faculty, or from working with classmates
You get the benefit of your junior's labor :)
Upperclassman: I wonder what a model of X would look like
You (2 days later): Wrote that and solved it, here are some CS
Upperclassman: Wonder what the effect of X on Y is
You: yo, I just pulled ACS data and ran some regressions on it, what to do next
That said I've seen it work: just my personal $0.02
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When the university starts sending out teaching evaluation reminders, I tell all my classes about bias in teaching evals, with links to the evidence. Here's a version of the email I send, in case anyone else wants to poach from it.
1/16
When I say "anyone": needless to say, the people who are benefitting from the bias (like me) are the ones who should helping to correct it. Men in math, this is your job! Of course, it should also be dealt with at the institutional level, not just ad hoc.
OK, on to my email:
2/16
"You may have received automated reminders about course evals this fall. I encourage you to fill the evals out. I'd be particularly grateful for written feedback about what worked for you in the class, what was difficult, & how you ultimately spent your time for this class.
3/16
However, I don't feel comfortable just sending you an email saying: "please take the time to evaluate me". I do think student evaluations of teachers can be valuable: I have made changes to my teaching style as a direct result of comments from student teaching evaluations.
4/16
But teaching evaluations have a weakness: they are not an unbiased estimator of teaching quality. There is strong evidence that teaching evals tend to favour men over women, and that teaching evals tend to favour white instructors over non-white instructors.
5/16
1/16
When a teaching award is based solely on teaching evals and then only men get it. pic.twitter.com/szIBkCvTe9
— Dr. Marissa Kawehi (@MarissaKawehi) February 12, 2021
When I say "anyone": needless to say, the people who are benefitting from the bias (like me) are the ones who should helping to correct it. Men in math, this is your job! Of course, it should also be dealt with at the institutional level, not just ad hoc.
OK, on to my email:
2/16
"You may have received automated reminders about course evals this fall. I encourage you to fill the evals out. I'd be particularly grateful for written feedback about what worked for you in the class, what was difficult, & how you ultimately spent your time for this class.
3/16
However, I don't feel comfortable just sending you an email saying: "please take the time to evaluate me". I do think student evaluations of teachers can be valuable: I have made changes to my teaching style as a direct result of comments from student teaching evaluations.
4/16
But teaching evaluations have a weakness: they are not an unbiased estimator of teaching quality. There is strong evidence that teaching evals tend to favour men over women, and that teaching evals tend to favour white instructors over non-white instructors.
5/16