Researchers who do activist science: who should I read to learn the gold standard for doing such research?
@justinmogilski
Associate Professor of Psychology. I use evolutionary theory to study the conflict resolution strategies of people with multiple intimate partners. https://www.researchgate.net/profile/Justin-Mogilski https://truebut.substack.com?r=25rst1&utm_medium=ios
Researchers who do activist science: who should I read to learn the gold standard for doing such research?
#SPSP2026
you can reason through this stuff for yourself, and possibly decide that certain approaches are not relevant or are not well-supported by evidence. *But at least you thought about it*
This is definitely the way to do it. Iβll be checking back periodically on its progress.
is that the decision tree they provide leads to articles. In other words, these are not opaque recommendations. They redirect you to the research published in the area (which, at times, appears to be nothing!). This way,
Anyone interested in DEI, I stumbled on this resource today:
psychgrail.com/resources/
It is a young (incomplete) effort to compile the considerations social scientists ought to make to reduce structural (and other) barriers to DEI in their research design and implementation.
What I likeβ¦
Isnβt this true of nearly every social science journal? How do we know this is an ev psych problem?
I actually bought the book as soon as it came out, but havenβt read. Paulβs work was influential to my PhD work. Iβll give it a read before I judge more.
Hmm, tbh, this feels like a mischaracterization of the best that the field has to offer. It definitely goes after low hanging fruit and ignores a lot else.
Yeah, I wonder about the quality of those 30 reviews.
The careful authors love me because I read what they write. The industrial authors hate me because I read what they write π
I now only review papers if I am interested in the content and it is directly relevant to my active research.
That said, 3-4 per semester. It was more before tenure.
Also, this is a pretty good condensation of the definitions that we provide.
This is an oddly thoughtful read about the aftermath of DEI from an Afrofuturism perspective. It's a humble hybrid of perspectives and research methods.
Most importantly, it cites me in the first sentence to define DEI. www.mdpi.com/2076-0760/14...
My messaging policy until January
Ever wonder how people in open relationships actually make it work? Justin Mogilski is back on the show to break down what the research says. https://www.sexandpsychology.com/blog/podcast/episode-453-the-secrets-to-a-successful-open-relationship/
Does CNM = cheating? In this episode, Dr. Justin Mogilski breaks down why people often confuse consensual non-monogamy with infidelity, and what the research actually says. https://www.sexandpsychology.com/blog/podcast/episode-452-what-people-get-wrong-about-open-relationships/
These summarize my key points about infidelity.
Part 3 is now live π
Here, I discuss what we learned about infidelity from our data, and why I think CNM is a better way of having multiple partners than infidelity.
Link and notable excerpts below:
I solemnly swear to use this as a cudgel against anyone who makes poor criticisms of DEI programming βοΈπ‘οΈ
Summary thread: bsky.app/profile/just...
Our adversarial collaboration is now published.
"Defining diversity, equity, and inclusion (DEI) by the scientific (de)merits of its programming"
In Theory & Society.
Thank you to my incisive coauthors: Lee Jussim, Anne Wilson, Bryan Love
π§΅below
t.co/RMfzBfraA7
Shoutout to Dr. Cory Clark, co-editor for this special issue on normative scientific conflicts, who nudged me to write this.
If youβd like to read the full paper, you can find the preprint here:
osf.io/4cp7y
Each author has said thereβs something in here that makes them uncomfortable, but they approve of the final product.
In other words, this adversarial collaboration was a success π
Based on our review, we make several recommendations to improve the scientific study of DEI programming.
We conclude that everyone (pro- and anti-DEI alike) can do better:
Though, there have been exceptions.
Here in the paper, we review some of these research literatures, and note the strengths and limitations of: affirmative action, Critical Race Theory, and bias reduction interventions (including diversity statements).
For much of DEIβs history, this has not been how programming was evaluated.
Having defined, measurable, and standard outcomes permits better testing of DEI programming because it provides common language and procedure for adjudicating which programs are worthwhile, and why.
To assist in this effort, we offer definitions of D, E, and I that are focused on their intended humanitarian outcome.
We arrived at these by reviewing and critiquing several recent popular perspectives. But, of course, these should be modified as scientific consensus shifts.
This is the meat of the paper:
If you want to test whether something works (or not!), you need to specify how by modeling the network of causal variables presumed to connect independent to dependent variables.
Then, you evaluate competing models.
We contend that these are each reasonable positions but often donβt make contact because DEI is neither standardly defined nor are its outcomes and mechanisms of action standardly evaluated.
We first steel man each sideβs arguments.
Pro-DEI argues for the humanistic ideals and effectiveness of such programming.
Anti-DEI argues that such programming is ineffective, costly and, at least in some cases, antithetical to its original aims.