All I can come up with is discrediting cheap and effective interventions to peddle your own snake oil.

I was in a meeting where the facilitator would stop presenting to say out loud when she noticed someone in the process of typing a comment in the chat 😭

Same. It’s mostly worth it but I have had some nasty surprises. 🤣

They made a FB event!

Why does he have 7 different reasons and none of them make sense. What is the actual reason. 🤨

I got the email. Assumed it was everyone.

😂 you could probably pin it yourself and then just hand it over.

I use a tailor for ~$20 because I hate sewing.

Cancelled NIH grant information submission form Please use this form to submit information identifying specific NIH grants that have been cancelled for any reason after January 20, 2025. Data from this form will be used to update the Rescinded NIH...

We've been tracking unlawful NIH grant terminations for 3 weeks. Spread the word👇!

Fellow PIs: what can you do upon termination?
✅ Email PO + document questions
✅ Submit FOIA
✅ Advocate to your OCG/OSP for appeal + litigation
✅ Consider outside litigation
✅ Donate to state AGs + legal orgs

1/🧵

Haha yes I see friends down south posting salads made from their gardens while it’s still snowing here.

This award no longer effectuates agency priorities. Research programs based primarily on artificial and non-scientific categories, including amorphous equity objectives, are antithetical to the scientific inquiry, do nothing to expand our knowledge of living systems, provide low returns on investment, and ultimately do not enhance health, lengthen life, or reduce illness. Worse, so-called diversity, equity, and inclusion (“DEI”) studies are often used to support unlawful discrimination on the basis of race and other protected characteristics, which harms the health of Americans. Therefore, it is the policy of NIH not to prioritize such research programs.

My federal grants with @wendymanning.bsky.social and Ann Meier were terminated last week. The language from the termination is below. It has been sad as we are being forced to say goodbye to members of our team. We are figuring out next steps. We remain deeply committed to studying all families.

A couple years ago U of MN was intentionally poaching researchers from politically conservative states. And now they announced that political stances are against university policy. Sobering stuff.

I referred to it as a “cervical cancer vaccine” and my friend was like there’s a cervical cancer vaccine?? Just didn’t make the connection even though she received it

Thanks for reading, Mary!

They are unionized. Some of the firings target people in their probationary period before full union protections kick in. Some of the firings are illegal.

your Ward 2018 AEP paper is cited, as always!

Thanks for pointing that out! I changed my settings so you should be able to now. Looks like I can't DM you since you don't follow me.

See full commentary for more details on each of these recommendations, additional ethical and statistical justifications, and a treasure trove of citations.

Resist by continuing to move your work forward!

Knee jerk “insufficient sample size” justifications for failing to collect and analyze data on marginalized communities is dismissive and harmful.

If our standard practices systematically disadvantage minoritized groups, then we need to find ways to correct them.

Data owners Rec 3: Become familiar with data ownership frameworks outside of the mainstream.

Mainstream frameworks for data ownership and ethics emphasize concerns about privacy and statistical rigor (aka prioritize sample size), while complementary frameworks emphasize other value systems.

Data owners Rec 2: Reconsider sample size requirements with the size of marginalized populations in mind.

Some marginalized groups simply do not exist in numbers large enough to satisfy sample size req's.

In these cases, are we willing to exclude entire communities from the scope of statistics?

Data owners Rec 1: Facilitate the implementation of the above recommendations.

Structural racism researchers encounter structural racism in their efforts to obtain data.

Data owners should allow researchers to make a case for analyzing smaller samples than are customary to with their dataset.

Rec 5b: Avoid analyzing or reporting “multi-racial” as racial/ethnic category.

It is so vague it is meaningless.

One option is to create categories for combos of racial and ethnic groups which exhibit distinct health patterns.

Another option is categories that are not mutually exclusive.

Rec 5a: Avoid analyzing or reporting “other” as racial/ethnic category.

An “other” estimate is just a weighted average, weighted toward whichever remaining group happens to be the largest in that particular dataset – a group which is rarely identified.

Rec 4: Publish estimates produced from small samples of marginalized groups even if they are imprecise.

In isolation, imprecise estimates might not be convincing, but if several publications produce similar estimates, we essentially increase the sample size and make progress toward precision.

Rec 3: Explore ways to thoughtfully increase the analytic sample of the group you’re interested in.

In situation when sample sizes from marginalized groups are too small to analyze with bivariates or regression models, thoughtfully consider who else is similar enough to be categorized together.

Rec 2: Report overall Ns of each racial/ethnic subgroup in your data, even if you do not analyze them further.

This encourages transparency.

Many papers report race/ethnicity data in a way that the reader cannot assess whether it was justifiable to exclude or combine racial/ethnic groups.

Rec 1: Recognize that descriptive analyses have smaller sample size req's.

Rules of thumb for sample sizes assume the goal is multivariable models. Descriptive epi is essential to address health inequities.

And exposures more common among marginalized groups are in earlier stages of research.

It is worth revisiting whether common practices around sample size requirements in observational data are actually best practices or not, and whether they strike the right balance between privacy and our ability to document the experiences of marginalized groups.

As social epidemiologists, we use epidemiologic methods to study racism within structures such as housing, education, and the criminal legal system.

But we also need to examine racism within structures in our own field.