naomithyden.bsky.social
Social Epidemiologist
Research: structural racism, policy, life course
WNBA fan. 4th Gen Japanese American and WOC. She/her.
đź“ŤMinneapolis
23 posts
186 followers
618 following
Regular Contributor
Active Commenter
comment in response to
post
Thanks for reading, Mary!
comment in response to
post
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.
comment in response to
post
your Ward 2018 AEP paper is cited, as always!
comment in response to
post
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.
comment in response to
post
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!
comment in response to
post
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.
comment in response to
post
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.
comment in response to
post
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?
comment in response to
post
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.
comment in response to
post
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.
comment in response to
post
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.
comment in response to
post
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.
comment in response to
post
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.
comment in response to
post
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.
comment in response to
post
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.
comment in response to
post
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.
comment in response to
post
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.
comment in response to
post
We know we need disaggregated data on minoritized groups - Indigenous Peoples, AAPI, sexual and gender minorities, Black immigrants, etc.
Yet it is common practice to exclude and obscure these groups in population-level analyses because of 'insufficient sample size'.
comment in response to
post
The social media comments about this have been vile!
comment in response to
post
I didn’t know Howe or Cooper were neighborhoods until just now 🤷🏻‍♀️