Author | Lightnews

Eli Holder

@elibryan.bsky.social

2.6K followers 4.5K following 310 posts

Raleigh. How might we visualize people, fairly and equitably? Data / dataviz / design / psychology / research geek. He / him. Chaotic good. Follows Fizzlethorpe Bristlebane. Design / research / writing at https://3iap.com.

3iap.com.

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Eli Holder @elibryan.bsky.social · Oct 17

Excited to share my new study with Lace Padilla, re: equity impacts of public health dataviz. #ieeevis 📊

The bad news: Conventional disparity charts may actively undermine health + health equity. They push misbeliefs about the people being visualized.

The good news: ...

osf.io/preprints/os...

A population health bar chart showing disparities in heart disease between social (racial) groups with text: "Can we do better?"

The "hunch" for our Must Be A Tuesday study. An alternative design could be "better" than conventional designs for communicating health equity issues, where "better" is 1) offsetting blame and stereotyping and 2) having similar impacts on more typical health communication goals like risk perception, behavioral intent, and policy support.

The 8 stimuli we tested, crossing "geo emphasized" vs "conventional bars", heart disease vs liver disease, racial groups vs abstract letter groups.

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Karen Tumulty @ktumulty.bsky.social · 14d

My favorite sign at the Montclair NJ No Kings today:

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Roy Cooper @roycoopernc.bsky.social · 14d

A trip to the doctor after an accident shouldn’t cost so much that you can’t pay your rent. We expanded Medicaid so working people can have peace of mind, knowing an illness or injury won’t put them in debt. DC Republicans including my opponent clearly disagree.

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Elizabeth Bonawitz @ebonawitz.bsky.social · 17d

eh, It wasn't that high up... and 4-year-olds can take it. 😜

But if you're looking for other good moments in the paper... I also recommend reading the acknowledgments closely.

The acknowledgment section of a paper stating that the construction crew at Rutgers drilled a hole in the lab and dumped several pounds of concrete on the stimuli

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Electronic Frontier Foundation @eff.org · Oct 2

Turn off your phone’s “advertising ID” to make it harder for location data brokers to track you. (2/4)

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Till Eckert @tilleckert.com · Sep 26

1/ I’m Till Eckert, a ProPublica reporter. For the past 2 weeks, I’ve been going to the same NY immigration courthouse.

Nearly every time, I see ICE agents arresting immigrants. Today, a woman was slammed to the ground after begging officials not to take her husband away.

Thread 👇

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Data Visualization Society @datavizsociety.bsky.social · Sep 23

📊 The new book Dashboards That Deliver releases today. For authors Andy Cotgreave, Amanda Makulec, Jeffrey Shaffer, and Steve Wexler, this is the culmination of countless hard work.

@emiliaruzicka.bsky.social sat down with the authors to hear about their process.

nightingaledvs.com/behind-the-s...

Behind the Scenes: Dashboards That Deliver, Nightingale

Andy Cotgreave, Amanda Makulec, Jeffrey Shaffer, and Steve Wexler have a new book coming out on September 23, 2025—Dashboards That Deliver: How to...

nightingaledvs.com

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Hooper @hooperhooper.bsky.social · Sep 18

Last year I wrote about the NCGOP leaderships multi-decade obsession with erasing LGBT people from UNC’s campus life for @triangleblogblog.bsky.social. Might need to update soon unfortunately. triangleblogblog.com/2024/05/05/t...

The long and eventful history of Tim Moore and Peter Hans’ animosity towards marginalized people - Triangle Blog Blog

A group civics blog covering town council, education, transportation, and recreation in Chapel Hill and Carrboro, NC.

triangleblogblog.com

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Ana Marie Cox @anamariecox.bsky.social · Sep 18

Disney learned nothing from Andor.

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Eli Holder @elibryan.bsky.social · Sep 15

Kinda like pufferfish sushi... good if you get it right, but one wrong slice and ☠️☠️☠️!!

Eli Holder @elibryan.bsky.social · Sep 9

Appreciate this analysis! Is the trend related to any particular component of the deprivation index more than others? Not sure from this dataset if that's an easy thing to break out, but I'd be curious how this tracks with housing?

Eli Holder @elibryan.bsky.social · Sep 9

🤩📊 What a cool visual effect! Great composition from @nrennie.bsky.social

Nicola Rennie @nrennie.bsky.social · Sep 9

There was lots of data to play with for #TidyTuesday this week where we're looking at the power of different passports! ✈️

I decided to try out the idea of using small multiples and highlighting to untangle a spaghetti chart with lots of lines 📊

#RStats #DataViz #ggplot2

Chart showing how rankings of passports have changed over time, split by region with top one in each highlighted. European are ranked high, and UAE has had a dramatic rise.

Eli Holder @elibryan.bsky.social · Sep 9

The Times takes their horse race reporting about as seriously as you should... which is.... not at all. 🏇📊

Voilà: Francis Gagnon @chezvoila.com · Sep 9

I just had to check it for myself: the NYT truly only compressed Mamdani to fit into the mobile version, and none of the others. 📊 #dataviz

No matter the technical explanation, the could and should have been avoided.

Reposted by Eli Holder

Voilà: Francis Gagnon @chezvoila.com · Sep 1

Rosling’s insistance on looking beyond averages to see the world as it really is reminds me of the work of @elibryan.bsky.social and Cindy Xiong. 📊

nightingaledvs.com/unfair-compa...

Top left: line chart of math scores from 1965 to 2015 comparing men and women where men are slightly higher throughout.

To right: similar line chart comparing the average income per day of US and Mexico from 1965 to 2015 where US is higher throughout.

Now let's look at the same data in a third way. Instead of looking at the averages each year, let's look at the range of math scores, or incomes, in one particular year.

Left: area chart of number of individuals with different math scores 2016, separating men and women, who mostly overlap.

Right: Number of individuals with different incomes 2016 where Mexico overlaps in the middle with the US.

Now we get a sense of all the individuals who were bundled into the average number. Look! There is an almost complete overlap between men and women's math scores. The majority of women have a male math twin: a man with the same math score as they do. When it comes to incomes in Mexico and the United States, the overlap is there but it is only partial. What is clear, though, looking at the data this way is that the two groups of people — men and women, Mexicans and people living in the United States — are not separate at all. They over-lap. There is no gap.
Of course, gap stories can reflect reality, In apartheid South Africa,

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Eli Holder @elibryan.bsky.social · Sep 4

Go for broke! Log scaling!

Eli Holder @elibryan.bsky.social · Sep 3

Fun sketches → Fun charts! 📊🎉

Pencil sketch of a diverging area chart with annotations

Pencil sketch of some kind of jitter plot

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Marianne Dahl @mariannedahl.bsky.social · Aug 29

📊 New dataset and paper alert!
We’re proud to launch the Opposition Movements and Groups (OMG) Dataset, 1789–2019: a global dataset covering 1,452 mass mobilization movements. It was just published in Comparative Political Studies. journals.sagepub.com/doi/10.1177/...

Below follows a 🧵

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Eli Holder @elibryan.bsky.social · Aug 25

Thanks for sharing RJ!

Eli Holder @elibryan.bsky.social · Aug 25

Appreciate it! This specific talk wasn't recorded, but...

My last public talk for "R Ladies" covered similar material: 3iap.com/rladies2025/

I'm also generally available for team workshops, if that's helpful: 3iap.com/workshops/eq...

The SIGGRAPH abstract has notes: doi.org/10.1145/3721...

R Ladies Rome Talk: Deathly Dataviz

Deathly Dataviz: How Public Health Dashboards Can Backfire, and What We Can Do Instead. A presentation for R Ladies Rome.

3iap.com

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Eli Holder @elibryan.bsky.social · Aug 24

What can we do here?

@elijfinkel.bsky.social speed dating work suggests a much less bleak dating world, vs Tinder's 80/20 dynamic: doi.org/10.70400/NEL...

@jamieamemiya.bsky.social & co suggest counterfactuals to blame systems, not people: doi.org/10.1177/1745...

Which maybe looks like this...

A quote describing Eli J. Finkel’s “Actor, Partner, Relationship” model of attraction. It reads: “Rather than having the 10s match with the 10s... most of us can find a partner who is something close to a 10 for us.”

There’s also a figure loosely illustrating this, with lots of people matching with lots of other people.

a bar chart showing swiping / liking behavior on tinder between different gender groups

text says: “Better: Blame tinder, not women” a play on “Blame systems, not people”

The original bar chart showing swiping / liking behavior on tinder between different gender groups, paired with a counterfactual bar chart showing liking behavior in speed dates for different gender groups.

The title says “Tinder Distorts Dating Behavior”

Eli Holder @elibryan.bsky.social · Aug 24

Genetic determinism also shows up in incel belief systems, tangled up with some wild takes on online dating statistics... (e.g. women's suspected urge to "trade up" beyond their "looksmatch").

Preston & co: doi.org/10.1177/1097...
Vallerga & Zurbriggen: doi.org/10.1111/asap...

Slide showing Sydney Sweeney beside the Jamie Miller character from Netflix’s “Adolescence” series

Beside Sweeney is text: “Sydney Sweeney is genetically superior”
Beside Miller is text “Others are genetically inferior.”

This concept of genetic worth is part of both eugenics and the incel belief system

Slide showing a fake statistical statement about inequality in dating: “80% of women are only interested in the top 20% of men. So 80% of men have to fight for the bottom 20% of women.”

Beside it is a bar chart showing swiping / liking behavior on tinder between different gender groups, which are interpreted among incels as evidence of women’s “hypergamy”

A bar chart showing swiping / liking behavior on tinder between different gender groups. A figure loosely illustrating the presumed lookism 80 / 20 rule “80% of women are only interested in the top 20% of men. So 80% of men have to fight for the bottom 20% of women.”

To the right are different explanations offered for these disparities (and lack of dates)

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Eli Holder @elibryan.bsky.social · Aug 22

What can we do (for the charts)? Part of the misattributions stem from design choices.

❌ Bar charts increased genetic and personal blame for health disparities.

✅ These "geo-emphasized" jitter plots shifted blame toward systemic explanations.

Links + videos from our last paper: 3iap.com/mbat/

Slide showing a bar chart of public health disparities with the text “Save lives. Stop bar charts.”

From my deathly dataviz talk: https://3iap.com/rladies2025/

Slide showing the “geo emphasis” chart from our must be a tuesday study, with text “We can do better”

From must be a tuesday study: https://3iap.com/mbat/

How did viewers explain health disparities in our Must Be A Tuesday study (https://3iap.com/mbat/)? It shows that conventional bar charts significantly increased genetic attribution and personal blame. And that the geo-emphasis charts significantly shifted blame from personal toward external attributions.

Slide shows a simplisitc chart of outcomes, hiding variability, which says “less of this”
And a more complete jitter plot of outcomes, showing variability, which says “more of this”

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Eli Holder @elibryan.bsky.social · Aug 22

Similar stories here:

Good outcomes = good genes
→ "Do Black people really need vaccines or anesthesia?"

Bad outcomes = bad genes
→ "There's nothing we can do to help!"

These charts are obviously well-intended, but ours + other studies find that viewers often misattribute these disparities.

Demonstrating viewers’ explanations for health disparities based on viewing health disparity charts.

They often blame people (personal attribution) by explaining the disparities in terms of personal behavior or characteristics “Drinking and smoking”, “too much fried food”, “bad genes.” These may make sense at individual levels, but not for populations.

Or you could attribute these disparities to external social determinants of health like “access to care, good food”, “neighborhood pollution”, “structural racism”

quotes are paraphrased from qual responses seen in the “Must be a Tuesday” study https://doi.org/10.1109/VIS55277.2024.00021

Tracing a theory of action for how genetic misattributions can build into other beliefs that ultimately lead to tangible real world outcomes, like Black patients being misdiagnosed when presenting with pain.

From my deathly dataviz talk: https://3iap.com/rladies2025/

RFK Jr’s statement about Black vs White vaccine schedules. It shows his quote: “We should not be giving Black people the same vaccine schedule that’s given to whites, because their immune system is better than ours.”

Two news headlines showing Sen Roger Marshall and Sen Bill Cassidy blaming public health problems on individuals.

They read:
“GOP Senator Blames Americans For Most Of Their Health Problems”
https://www.rollingstone.com/politics/politics-news/roger-marshall-make-america-healthy-again-1235232716/

“Maternal death rate isn’t as bad if you don’t count Black women, GOP senator says”
https://www.businessinsider.com/gop-senator-la-outlier-maternal-death-rate-skewed-black-women-2022-5

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Eli Holder @elibryan.bsky.social · Aug 22

Similar story here:

Good outcomes = good behavior (us)
→ Bad outcomes = bad behavior (others)
→ "Should we spend so much $$$ vaccinating people who don't deserve it?"

A quote from RFK Jr “It’s exceedingly difficult for measles to kill a healthy individual ...there’s a connection between those who suffer from measles and individuals who lack proper nutrition or don’t engage in regular physical activity.”

A quote from Dr Oz, head of medicaid, “It’s your patriotic duty to be as healthy as you can.”

Two quotes from Attwell et al 2018’s focus group study of anti-vaxers.

Attwell et al 2018 ‘The Unhealthy Other’ How vaccine rejecting parents construct the vaccinating mainstream. https://doi.org/10.1016/j.vaccine.2018.01.076

News headline announcing cuts to mRNA vaccine research. It reads: RFK Jr cancels $500m in funding for mRNA vaccines for diseases like Covid”

https://www.bbc.com/news/articles/c74dzdddvmjo

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Eli Holder @elibryan.bsky.social · Aug 22

How does this work for the lame jeans/genes ad? What's the argument behind the ad? What makes it funny (to some people)? Where does it lead?

Good jeans → Good genes (us) → Bad genes (others) → "haha our genes _are_ great!" → "What if we ranked people based on genetics?!"

Slide with a photo from the American Eagle “good genes” ad with the subtext as actual text: “Sydney Sweeney is genetically superior”

Slide on the rhetoric of the “good genes” american eagle ad. It says “Genetic superiority is definitely a real thing. Hint: It isn’t.” It shows the eugenicist Karl Pearson looking excited and pointing to Sydney Sweeney.

Slide visualizing the eugenic idea that people can be stack ranked based on some simplistic unilinear concept of genetics. On the left it shows “genetically inferior” with an Elphaba-esque woman. On the right it shows “genetically superior” with the american eagle model

Slide with a fake photo of Sydney Sweeney holding up a bottle of bleach spray. It says “Sydney Sweeney supports sterilization... of kitchen surfaces.” The risk of dog-whistle ads is maybe clearer when considering where this kind of rhetoric has led historically, e.g. sterilization programs and genocide.

Eli Holder @elibryan.bsky.social · Aug 22

What do these have in common? It's not what they "say," it's "what do they suggest?"

They suggest a world where "genes are destiny."

They're blame-framed, so looks, love, and health can seem like immutable personal characteristics, rather than results of big messy social forces.

applying the "woke" critical analysis framework to the jeans ad. What does the ad claim technically? What does it suggest? How might people act on it?

Applying the rhetorical analysis framework to the health risk charts we tested in “Must be a Tuesday” https://doi.org/10.1109/VIS55277.2024.00021

It shows a bar chart with heart disease mortality for four different groups (which are stand ins for racial outcomes). It asks what does the chart suggest to some people about why heart disease mortality is higher for people in Group B?

applying the framework to a bar chart showing swiping / liking behavior on tinder between different gender groups. What does the chart show technically? What does it suggest? How might people act on it?

Applying the framework to RFK Jr’s statements about Black vs White vaccine schedules. It shows his quote: “We should not be giving Black people the same vaccine schedule that’s given to whites, because their immune system is better than ours.” and asks what does this suggest?

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