Nils Reimer

I am hoping to recruit a Ph.D. student to join the SPARC (Social Psychology of Activism, Resistance, & Change) Lab at @UVAPsyc in Fall 2026! You can find more info about my research on my website (ericshuman.com), and the program here (psychology.as.virginia.edu/social-psych...).

Interested in models used to estimate lagged effects in panel data? We (@rebiweidmann.bsky.social, Hyewon Yang) have a new paper looking at patterns of stability and their implications for bias and model choice: osf.io/preprints/ps... [1/x]

UCSB Campus. Meadow in the foreground with Storke Tower and mountains in the distance

Spread the word: I'm looking to recruit a PhD student for Fall 2026 to @ucsb.bsky.social! Reach out if you are applying this cycle and hoping to study infant and child social cognition, specifically expectations about friendship and/or groups. Bonus: live in paradise! And.. 1/3

A lot of people think that every international student admitted means one fewer spot for domestic students, when the opposite is more likely true - the tuition revenue international students bring allows public universities to provide substantial discounts to domestic students, improving access.

Congratulations!

I cannot tell you how grim the AI in higher ed situation is. Many of the students have completely surrendered to letting AI do their homework, badly, I might add. How do you fix this? Truly, what the hell do we do, beyond what grading can address, which isn't a solution?

If you can't be bothered to read, why are trying to be a scientist. Baffling...

UC employees, not waiting on leaders, sue Trump for 'financial coercion' over UCLA cuts University of California faculty, students and staff on Tuesday sued President Trump over a $1.2-million penalty against UCLA and federal demands over campus changes. They argued that the actions camp...

Facing a proposed $1.2-billion fine and severe medical research grant cuts at UCLA, the University of California has not gone head-to-head with Trump in court.

So on Tuesday, groups representing more than 100,000 of its employees did.

www.latimes.com/california/s...

I wrote a little note on awards for diversity and science:
mwkraus.medium.com/a-note-on-aw...

Opinion | When Universities Become Informants A practice from the McCarthy era makes an ugly return.

Judith Butler: "It is important to refuse the notion that this is just how things are right now, invoking a feckless realpolitik that justifies complicity with a brutal and rising authoritarianism."

I have many thoughts about Charlie Kirk—and perhaps even more about the white elites, including some on the left, who insist we can’t hold multiple realities at once. We can. And we must.

A brief 🧵

ggplot2 4.0.0 A new major version of ggplot2 has been released on CRAN. Find out what is new here.

I am beyond excited to announce that ggplot2 4.0.0 has just landed on CRAN.

It's not every day we have a new major #ggplot2 release but it is a fitting 18 year birthday present for the package.

Get an overview of the release in this blog post and be on the lookout for more in-depth posts #rstats

Pseudo Effects: How Method Biases Can Produce Spurious Findings About Close Relationships - Samantha Joel, John K. Sakaluk, James J. Kim, Devinder Khera, Helena Yuchen Qin, Sarah C. E. Stanton, 2025 Research on interpersonal relationships frequently relies on accurate self-reporting across various relationship facets (e.g., conflict, trust, appreciation). Y...

In a new paper, my colleagues and I set out to demonstrate how method biases can create spurious findings in relationship science, by using a seemingly meaningless scale (e.g., "My relationship has very good Saturn") to predict relationship outcomes. journals.sagepub.com/doi/10.1177/...

Since the 1970s, the conservative legal movement has worked to re-segregate society. Sometimes they use claims of race-neutrality to achieve a specific goal (ending affirmative action). Other times they use explicit racism (mass deportation). But these tactics all serve the aim of re-segregation.

Abstract: Under the banner of progress, products have been uncritically adopted or even imposed on users — in past centuries with tobacco and combustion engines, and in the 21st with social media. For these collective blunders, we now regret our involvement or apathy as scientists, and society struggles to put the genie back in the bottle. Currently, we are similarly entangled with artificial intelligence (AI) technology. For example, software updates are rolled out seamlessly and non-consensually, Microsoft Office is bundled with chatbots, and we, our students, and our employers have had no say, as it is not considered a valid position to reject AI technologies in our teaching and research. This is why in June 2025, we co-authored an Open Letter calling on our employers to reverse and rethink their stance on uncritically adopting AI technologies. In this position piece, we expound on why universities must take their role seriously toa) counter the technology industry’s marketing, hype, and harm; and to b) safeguard higher education, critical thinking, expertise, academic freedom, and scientific integrity. We include pointers to relevant work to further inform our colleagues.

Figure 1. A cartoon set theoretic view on various terms (see Table 1) used when discussing the superset AI (black outline, hatched background): LLMs are in orange; ANNs are in magenta; generative models are in blue; and finally, chatbots are in green. Where these intersect, the colours reflect that, e.g. generative adversarial network (GAN) and Boltzmann machine (BM) models are in the purple subset because they are both generative and ANNs. In the case of proprietary closed source models, e.g. OpenAI’s ChatGPT and Apple’s Siri, we cannot verify their implementation and so academics can only make educated guesses (cf. Dingemanse 2025). Undefined terms used above: BERT (Devlin et al. 2019); AlexNet (Krizhevsky et al. 2017); A.L.I.C.E. (Wallace 2009); ELIZA (Weizenbaum 1966); Jabberwacky (Twist 2003); linear discriminant analysis (LDA); quadratic discriminant analysis (QDA).

Table 1. Below some of the typical terminological disarray is untangled. Importantly, none of these terms are orthogonal nor do they exclusively pick out the types of products we may wish to critique or proscribe.

Protecting the Ecosystem of Human Knowledge: Five Principles

Finally! 🤩 Our position piece: Against the Uncritical Adoption of 'AI' Technologies in Academia:
doi.org/10.5281/zeno...

We unpick the tech industry’s marketing, hype, & harm; and we argue for safeguarding higher education, critical
thinking, expertise, academic freedom, & scientific integrity.
1/n

📣 🚨 Yale Psychology has 3 searches this year!

Links below:

Quantitative link: apply.interfolio.com/171903
Social link: apply.interfolio.com/171989
Clinical link: apply.interfolio.com/171970

I'm so excited for this book!

Opinion | The Moral Paralysis Facing Iranians Right Now

My new op-ed in the @nytimes.

I argue that Iranians are caught in a state of “moral paralysis,” a psychological trap set by the Islamic Republic itself. It pits two of our most sacred values against each other: liberation vs. self-determination. (1/2) www.nytimes.com/2025/06/28/o...

Late afternoon sun in Albert park

My dept at the University of Auckland (NZ) will be hiring in social psych at the junior level this cycle. Official ad to follow

It's a big research-active dept with fun colleagues, plus you can commute to uni on a boat, paired with a pleasant walk thru Albert Park (this pic from heading home today)

A racial reckoning? racial attitudes in the wake of the murder of George Floyd Andrew M. Engelhardt and Cindy D. Kam Abstract Did George Floyd’s murder and its ensuing protests produce a racial reckoning? Conventional social-science accounts, emphasizing the stability of racial attitudes, dismiss this possibility. In contrast, we theorize how these events may have altered Americans’ racial attitudes, in broadly progressive or in potentially countervailing ways across partisan and racial subgroups. An original content analysis of partisan media demonstrates how the information environment framed Black Americans before and after the summer of 2020. Then we examine temporal trends using three different attitude measures: most important problem judgments, explicit favorability towards Whites versus Blacks, and implicit associations. Challenging the conventional wisdom, our analyses demonstrate that racial attitudes changed following George Floyd’s murder, but in ways dependent upon attitude measure and population subgroup.

Figure 1 shows four scatterplots with Lowess smoothing lines comparing Fox (gray squares, gray line) and MSNBC (black circles, black line) coverage of Black Americans in 2020, with a vertical red line marking George Floyd’s murder on May 25. Top left (Daily Counts of Activism Frames): Both networks show a sharp spike in activism-related mentions immediately after Floyd’s murder, then declining through the year, with similar levels across Fox and MSNBC. Top right (Daily Proportion of Mentions containing Activism Frames): The share of mentions with activism frames rises briefly after Floyd’s murder for both networks but quickly declines, with no clear partisan difference. Bottom left (Daily Counts of Backlash Frames): Fox shows a much larger spike in backlash-related mentions (e.g., “violence,” “mob”) after May, while MSNBC increases more modestly. Bottom right (Daily Proportion of Mentions containing Backlash Frames): From June to October, nearly half of Fox’s mentions of Black Americans include backlash frames, roughly twice the rate of MSNBC, which remains lower throughout. Overall, the figure shows that while both networks used more activism frames immediately after Floyd’s murder, Fox emphasized backlash frames much more heavily than MSNBC in the following months.

Figure 2 shows six scatterplots with Lowess smoothing lines tracking mentions of racism or race relations as the most important problem in Gallup polls (2017–2021). Each dot is a monthly estimate, with a vertical red line marking George Floyd’s murder in May 2020. Top row: Full Sample: Mentions are low (under 5%) before 2020, then spike sharply in June 2020 (~16%) before falling but remaining above pre-2020 levels. Among Whites: Similar pattern as the full sample, with a ~10-point jump in June 2020, followed by a decline but remaining elevated relative to earlier years. Among Blacks: Higher baseline concern compared to Whites; mentions spike by ~21 points after Floyd’s murder and remain elevated through 2021. Bottom row: Among White Republicans: Very low pre-2020 mentions, a modest rise (~6 points) in June 2020, then rapid decline toward baseline. Among White Independents: Clear but moderate spike in June 2020, with some persistence above baseline. Among White Democrats: Low pre-2020 mentions, sharp June 2020 spike (~14 points), then decline but sustained higher levels through 2021. Overall, the figure shows a sharp discontinuity after Floyd’s murder across all groups, with the most sustained increases among Black respondents and White Democrats, and weaker persistence among White Republicans.

Figure 4 presents six scatterplots of predicted weekly average IAT D-scores for 2019 (gray squares, gray line) and 2020 (black circles, black line), with a vertical red line marking George Floyd’s murder on May 25. Higher D-scores indicate stronger implicit anti-Black bias. Top row: Full Sample: Bias was declining before Floyd’s murder and drops further afterward in 2020, diverging from 2019. Among Whites: A clear decline in D-scores appears after Floyd’s murder, with lower bias sustained through 2020. Among Blacks: No sharp discontinuity; scores remain stable across 2019 and 2020. Bottom row: Among White Conservatives: Noticeable decline in anti-Black bias after May 2020, sustained through the year. Among White Neutrals: A clear drop in bias after Floyd’s murder, somewhat larger than among liberals. Among White Liberals: Small decline in bias after May 2020, though less pronounced than among conservatives or neutrals. Overall, the figure shows that implicit anti-Black bias decreased among White respondents across ideological groups after Floyd’s murder, with larger reductions among conservatives and neutrals than liberals. Black respondents show little change, consistent with already low baseline bias.

“A racial reckoning?” New study by @amengel.bsky.social & Cindy Kam:

“Challenging the conventional wisdom, our analyses demonstrate that racial attitudes changed following George Floyd’s murder, but in ways dependent upon attitude measure and population subgroup.” www.cambridge.org/core/journal...

✨✨ I will be reviewing applications for the University of Minnesota psychology PhD program this fall!

Information for potential applicants can be found on my lab website: ringwaldlab.psych.umn.edu/join-lab

Please spread the word!

all killer no filler

#Psychjobs
My former institution Colby College is hiring a tenure track in intergroup relations, broadly defined & open to many psych areas (not just social). This is my replacement line. I truly enjoyed my time at Colby and it's a great dept! Happy to answer Qs if I can.
apply.interfolio.com/172552

The D.C. Safe and Beautiful Task Force established in Executive Order 14252 of March 27, 2025 (Making the District of Columbia Safe and Beautiful), shall establish an online portal for Americans with law enforcement or other relevant backgrounds and experience to apply to join Federal law enforcement entities to support the policy goals described in Executive Order 14333. Each law enforcement agency that is a member of the D.C. Safe and Beautiful Task Force, as well as other relevant components of the Department of Justice as the Attorney General determines, shall further, subject to the availability of appropriations and applicable law, immediately create and begin training, manning, hiring, and equipping a specialized unit that is dedicated to ensuring public safety and order in the Nation’s capital that can be deployed whenever the circumstances necessitate, and that could be deployed, subject to applicable law, in other cities where public safety and order has been lost. ( (ii) The Secretary of Defense shall immediately begin ensuring that each State’s Army National Guard and Air National Guard are resourced, trained, organized, and available to assist Federal, State, and local law enforcement in quelling civil disturbances and ensuring the public safety and order whenever the circumstances necessitate, as appropriate under law. In coordination with the respective adjutants general, the Secretary of Defense shall designate an appropriate number of each State’s trained National Guard members to be reasonably available for rapid mobilization for such purposes. In addition, the Secretary of Defense shall ensure the availability of a standing National Guard quick reaction force that shall be resourced, trained, and available for rapid nationwide deployment.

Today’s Executive Order creating a *nationwide* military “quick reaction force” and setting up an online portal to permit random fascist vigilantes to join soldiers is one of the scariest things I’ve seen in U.S. politics in my adult life. Why is it not getting more attention?

Models as Prediction Machines: How to Convert Confusing Coefficients into Clear Quantities Abstract Psychological researchers usually make sense of regression models by interpreting coefficient estimates directly. This works well enough for simple linear models, but is more challenging for more complex models with, for example, categorical variables, interactions, non-linearities, and hierarchical structures. Here, we introduce an alternative approach to making sense of statistical models. The central idea is to abstract away from the mechanics of estimation, and to treat models as “counterfactual prediction machines,” which are subsequently queried to estimate quantities and conduct tests that matter substantively. This workflow is model-agnostic; it can be applied in a consistent fashion to draw causal or descriptive inference from a wide range of models. We illustrate how to implement this workflow with the marginaleffects package, which supports over 100 different classes of models in R and Python, and present two worked examples. These examples show how the workflow can be applied across designs (e.g., observational study, randomized experiment) to answer different research questions (e.g., associations, causal effects, effect heterogeneity) while facing various challenges (e.g., controlling for confounders in a flexible manner, modelling ordinal outcomes, and interpreting non-linear models).

Figure illustrating model predictions. On the X-axis the predictor, annual gross income in Euro. On the Y-axis the outcome, predicted life satisfaction. A solid line marks the curve of predictions on which individual data points are marked as model-implied outcomes at incomes of interest. Comparing two such predictions gives us a comparison. We can also fit a tangent to the line of predictions, which illustrates the slope at any given point of the curve.

A figure illustrating various ways to include age as a predictor in a model. On the x-axis age (predictor), on the y-axis the outcome (model-implied importance of friends, including confidence intervals). Illustrated are 1. age as a categorical predictor, resultings in the predictions bouncing around a lot with wide confidence intervals 2. age as a linear predictor, which forces a straight line through the data points that has a very tight confidence band and 3. age splines, which lies somewhere in between as it smoothly follows the data but has more uncertainty than the straight line.

Ever stared at a table of regression coefficients & wondered what you're doing with your life?

Very excited to share this gentle introduction to another way of making sense of statistical models (w @vincentab.bsky.social)
Preprint: doi.org/10.31234/osf...
Website: j-rohrer.github.io/marginal-psy...

You can add up all the enjoyable pursuits of LLMs and the work productivity hacks and none of them, separately or together, will be more important than AI’s ecological costs or political disruption.

“We” is more important here.

President Trump Is Right About the Smithsonian The National Museum of African American History and Culture debuted a series to educate people on “a society that privileges white people and whiteness” —

Well, if you were wondering exactly which parts of history the Trump regime is going to purge from the Smithsonian museums, they've helpfully listed it out. It's exactly as fascistic as you've feared.
www.whitehouse.gov/articles/202...

It's publication day for our first paper out of the www.csinequality.org lab completed entirely at NU. To write it, we asked: what research in the social psychology of inequality do we like and why do we like it? The answer is this paper:

trying this with GPT-5 and charting new frontiers in gaslighting

Here’s some news that I’ve been waiting years to share: Robert Gifford, formerly a professor of environmental psychology at the University of Victoria, was fired for sexual misconduct and sexual… | Je... Here’s some news that I’ve been waiting years to share: Robert Gifford, formerly a professor of environmental psychology at the University of Victoria, was fired for sexual misconduct and sexual haras...

A prominent psychology professor was fired for sexual harassment. I know of many cases like this that have gone unreported or people are actively pressured to cover it up.

Read the full case and comments here: www.linkedin.com/feed/update/...