iiinova — where your digital self keeps evolving

Andrew Trexler @atrexler.com · 15/09/2026

We were so glad to have you! Come again soon!

Reposted by Andrew Trexler

Isabella Rebasso @isabellareb.bsky.social · 28/08/2026

New paper with Yanna Krupnikov out in Political Communication! 🎉 We know moral-emotional content ("moral outrage") spreads fast on social media. But does that mean people actually want to see it? We tested whether people select this content when given the choice - turns out, not really.

tandfonline.com

Rethinking Assumptions About Moral Content Selection: Moral-Emotional Content May Be Less Appealing Than Assumed

Recent work has shown that moral-emotional content spreads rapidly on social media platforms such as X (Twitter). These patterns have led to concerns that social media facilitates the spread of mor...

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Mark Copelovitch @mcopelov.bsky.social · 26/08/2026

I am on the environmental politics committee and also happy to chat at APSA!

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Andrew Trexler @atrexler.com · 26/08/2026

UW-Madison Poli Sci has THREE searches for TT assistant professors: Environmental politics: go.wisc.edu/1gk366 Chinese politics: go.wisc.edu/847082 American political thought: go.wisc.edu/lfwg6o I am not on any of the search committees, but happy to chat about the dept/UW/Madison/etc at APSA!

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Claire E. Robertson, PhD @crobertson500.bsky.social · 24/08/2026

Is social media truly making us more politically polarized, or does it simply over-represent our most extreme opinions? In our new preprint, @small-schulz.bsky.social and I present *punishing evidence* that social media systematically overrepresents users’ most extreme political opinions. 1/n

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Drew Engelhardt @amengel.bsky.social · 18/08/2026

Working on a dissertation in American political behavior and need money for survey research? Apply for a grant worth up to $15,000 from the Rapoport Family Foundation. They’re planning on awarding up to 15 grants this cycle. Deadline Oct. 21. www.rapoportfamilyfoundation.com/phdgrant

rapoportfamilyfoundation.com

Rapoport Doctoral Dissertation Grants

Supporting projects for PhD students doing political science research, democracy and social justice.

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Adam Bonica @adambonica.bsky.social · 16/08/2026

The fundraising texts you delete are working on someone. It’s infuriating and heartbreaking. An 85yo in Ohio gave more than double the value of his home. A 91yo in an Indianapolis senior facility gave 25K times. The DCCC/DSCC don’t just tolerate the spammers who exploit seniors. They take part.

data4democracy.substack.com

Hook and Squeeze

How Democratic consultants, committees, and party leaders built a fundraising spam pipeline that funnels money from a captive pool of elderly donors into their own operations.

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John V. Kane @uptonorwell.bsky.social · 13/08/2026

🚨Super excited to share this new WP with Joohye Jeong, @adamberinsky.bsky.social, Soong & Parker. We ask a simple but extremely practical Q for survey researchers: 𝐃𝐨𝐞𝐬 𝐢𝐭 𝐦𝐚𝐭𝐭𝐞𝐫 𝐰𝐡𝐞𝐫𝐞 𝐰𝐞 𝐩𝐥𝐚𝐜𝐞 𝐢𝐭𝐞𝐦𝐬/𝐞𝐱𝐩𝐞𝐫𝐢𝐦𝐞𝐧𝐭𝐬 𝐢𝐧 𝐨𝐮𝐫 𝐬𝐮𝐫𝐯𝐞𝐲? Answer: Not really, no. 👍

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mark brandt @mjbsp.bsky.social · 10/08/2026

New pub, led by Aymin Triki & in collab w/ @abbycassario.bsky.social, accepted at JESP! We found similarities in party cues among the left and the right when using representative samples of issues, although right-wing authoritarians may be an exception Other interesting findings follow!

Abstract of paper. It reads, How do people with different political ideologies process political information? Party cues are an
effect where people are more likely to support a policy position if they learn their party also
supports it, shifting their judgement in accordance with cues from their inparty and against their
outparty. This effect has been at the center of the debate over the psychological differences
between liberals and conservatives, with some scholars suggesting that differences in cognitive
styles between liberals and conservatives (e.g., rigidity, cognitive reflection) should result in
differences in party cue susceptibility. We advance this debate by measuring rigid cognitive
styles and applying a stimuli sampling approach to party cues across four preregistered
experiments (N’s per study > 1200). We found convincing evidence for ideological symmetries
in party cues in quota matched samples of Americans (Studies 1 & 2). In Studies 3 and 4, across
four measures of ideology and three self-report measures of cognitive rigidity, we found
ideological differences in self-reported rigidity in line with previous research. In Study 3, a
convenience sample, we found that conservatives were more likely to follow party cues.
However, Study 4, using a quota matched sample, found no ideological differences in cue
susceptibility, except with respect to right-wing authoritarianism. Exploratory analyses found
that when one group has greater prior awareness or stronger initial views on a topic, they show
smaller cueing effects. We conclude that while liberals and conservatives differ in cognitive
style, they largely share similar cognitive processes for interpreting and integrating political
information.

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Jay Van Bavel, PhD @jayvanbavel.bsky.social · 18/07/2026

We need to change norms around sexual harassment Yesterday Tessa West spoke up about a sexual harassment complaint she filed against John Jost. Not only is he a senior colleague in the dept of psychology, but he is one of the most prominant figures in the field of social and political psychology.

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Andrew Trexler @atrexler.com · 18/07/2026

I had a joke about Lethe, but I forget how it goes.

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American Political Science Review @apsrjournal.bsky.social · 14/07/2026

From our FirstView: New Evidence and Design Considerations for Repeated Measure Experiments in Survey Research by @dianamejordan.bsky.social, TRENT OLLERENSHAW and @atrexler.com. doi.org/10.1017/S000....

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Lauren (Palladino) Olson @lrpalladino.bsky.social · 08/07/2026

My first-ever solo-authored paper is out today (open access!) in @journalrep.bsky.social! What drives Americans to switch their presidential vote based on race over the last 3 elections? I show that it's not general racial warmth, it's changing beliefs about discrimination. (🧵 1/3)

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Petter Törnberg @pettertornberg.com · 07/07/2026

‘Polarization’ has become the master concept for diagnosing our current democratic crisis. But this is not polarization. It is the radicalization of the political right. By misdiagnosing it, we risk becoming complicit in the crisis. 🧵 Just out in Perspectives on Politics doi.org/10.1017/S153...

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turgut keskintürk @tkeskinturk.bsky.social · 18/06/2026

a new working paper with Chris Johnston & @stephenvaisey.com! we study issue opinions among a novel sample of 10-12-year-olds, showing that children, contrary to received wisdom, express reasonably structured preferences. a working paper here: tkeskinturk.github.io/poldevelopment.pdf

The Emerging Structure of Political Preferences in Childhood

Turgut Keskintürk, Christopher D. Johnston, Stephen Vaisey

June, 2026

Research on political development has largely overlooked the opinions children form before adolescence, and paid even less attention to their views on specific issues. In this article, we present an original survey of children aged 10 to 12, conducted in 2024–2025, that measures children’s opinions on several policy issues alongside evaluations of the 2024 presidential candidates and the two major parties. To situate children’s responses in context, we benchmark children against one of their parents, surveyed concurrently, and against the 2024 American National Election Study. We find that children express policy opinions more often than they identify with a party, that these opinions organize along the same left-right axis as adults, if less tightly, and that evaluations of candidates and parties anchor this emerging structure. These findings suggest that children form issue opinions far earlier than scholars have assumed, calling for renewed attention to childhood as a formative and consequential site of political development.

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Genevieve Bates @genbates.bsky.social · 16/06/2026

🚨 🚨Calling all #polisky grad students who presented at #ISA2026: I'm chairing the committee for the Human Rights Section’s Steven C Poe best grad student paper award. We are currently accepting nominations, including self-nominations, and all you have to do is email your paper to me!

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Andrew Trexler @atrexler.com · 12/06/2026

IMO the more relevant classic cite for this poll result is not Converse (1964), but rather Zaller and Feldman (1992).

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Andrew Trexler @atrexler.com · 12/06/2026

Seeing lots of "voters are dumb" takes on this, Converse laser-eyes, etc. Consider the survey-taking experience. Ppl see/interpret these individually and give atomized answers. Q1: What will make Ds electable? Move to center. Q2: Is D party radical? No. Q3: Your personal view? Socialism = good.

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Ross Dahlke @rossdahlke.bsky.social · 27/05/2026

New work with @ryanmoore.bsky.social in @digitaljournalism.bsky.social examines Americans' exposure to Pink Slime websites--partisan websites that masquerade as local news--and compares consumption levels to untrustworthy and genuine local news websites doi.org/10.1080/2167...

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Jon Green @jongreen.bsky.social · 19/05/2026

new WP (w/ @ntd.bsky.social): we use the case of Christian nationalism to make a broader point about "niche ideologies" in mass opinion research, and why you shouldn't scale them the same way you'd scale more general attitudes Link: osf.io/wbdut/files/...

Title: Niche Ideologies in the Mass Public: The Case of
Christian Nationalism
Authors: Jon Green, Nick Davis
Abstract: It is common in survey research to measure political attitudes by inferring latent dimensions along which all respondents can be scored. We argue that this approach is ill-suited for the study of “niche ideologies” that organize the beliefs of concentrated minorities within specific political domains. We support this argument with the case of Christian nationalism, which is theorized as an ideology but typically measured as an attitude. Across two survey samples, we show that response patterns are better explained by a process in which individuals endorse, reject, or are unfamiliar with clusters of beliefs associated with Christian nationalism than by processes in which responses are dimensional. We then demonstrate that measuring Christian
nationalism as an attitude can distort its relationship with theoretically relevant policy preferences. Our results clarify distinctions between attitudes and ideologies and offer suggestions for how to investigate other niche ideologies in mass opinion research.

Figure 1. Distributions of Posterior Probabilities by DGP. Group-based is strongly preferred (higher probabilities for vast majority of respondents) in both BRS and PRRI samples.

Figure 3: Ideological identification by DGP. The Rejecter group is majority liberal across both samples with few conservatives; the Adherent group is majority conservative across both samples with few liberals.

Figure 6: Comparing group- versus dimensional-based estimates of the relationship between Christian nationalism and abortion attitudes (PRRI 2022). All models control for age, education, race, gender, party identification, and ideological identification.

When Christian nationalism is measured as a single dimension factor, it has positive relationships with both support for overturning Roe v. Wade and for more restrictive abortion policy. But when Christian nationalism is measured via a group-based mixture, being in the Adherent (vs. Innocent) group is only positively associated with more restrictive abortion policy, but not with support for overturning Roe v. Wade.

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American Political Science Review @apsrjournal.bsky.social · 21/04/2026

From our FirstView: Threats and Commitments: International Tribunals and Domestic Trials in Peace Negotiations by @genbates.bsky.social. doi.org/10.1017/S000...

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Andrew Trexler @atrexler.com · 25/04/2026

Worth clarifying: N matters in the sense that the benefit to power from the % reduction in the SE decreases as N grows (see Fig 6). N matters little for the % change magnitude directly. For RQs about magnitude, absolute error is a more central consideration (see Fig 7).

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Andrew Trexler @atrexler.com · 25/04/2026

I think our general advice still holds re: when to use RMs vs PO designs and my guess is that this kind of instruction has a mostly marginal impact on the design effect either way. But would need data to be sure, of course.

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Andrew Trexler @atrexler.com · 25/04/2026

Thanks! Good question---not something we deploy so no empirical evidence to offer. But speculatively: depends on relative concern of consistency (expect attenuation) vs demand effects (no clear/general directional expectation) in setting. This language may depress the former but increase the latter.

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Andrew Trexler @atrexler.com · 24/04/2026

You are very kind to say so!

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Reposted by Andrew Trexler

Alexander Wuttke @kunkakom.bsky.social · 24/04/2026

Cumulative science at its best.

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Andrew Trexler @atrexler.com · 24/04/2026

Thanks for reading! We're very excited about this one; we were all grad students when this project began & it came a long way w/lots of help. Thanks to TESS, Rapoport, & Bass for $, to NORC for helping field, to many folks for helpful comments, & Scott/Geoff esp. throughout (true model replicatees)!

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Andrew Trexler @atrexler.com · 24/04/2026

We conclude RM designs serve as a better default than PO designs. Social science engages with small effects, is resource limited, & often concerns directional tests. RM designs are better in these settings, though cases remain where large-N PO designs are better (magnitude RQs, sensitive topics).

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Andrew Trexler @atrexler.com · 24/04/2026

In our last analysis, we use simulations grounded in our observed data to investigate the bias-precision tradeoff. RM designs always offer superior power; this benefit declines as N-per-arm gets large. Yet RMs will be more accurate to true ATEs in expectation unless PO designs are very well powered.

Figure 6 from the paper, which shows how statistical power changes as sample size, true ATE, and true design effect change. RM designs always offer superior power but this benefit is less meaningful with large samples.

Figure 7 from the paper, which shows how absolute error changes as sample size, true ATE, and true design effect change. RM designs are more accurate in expectation for small samples, true ATEs, and true attenuations; PO designs are superior when samples, true ATEs, and true attenuations are large.

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Andrew Trexler @atrexler.com · 24/04/2026

That said, we find initial evidence that the design effect increases as respondents are repeatedly exposed to RM designs within a single survey, and particularly when attitude-recall questions (asking Rs to recall their pre-treat attitude) are deployed. This has implications for omnibus surveys.

Table 5 from the paper, which shows nearly-monotonic increases in the design effect as respondents encounter more and more RM designs in a single survey.

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Andrew Trexler @atrexler.com · 24/04/2026

Second, we observe few differences in the design effect by sample type (prob/nonprob), design type (between-groups/within-subject), and even by how close together repeated measures appear. RM design effects are no worse when putting pre-treatment measure, treatment, post-treatment back-to-back.

Figure 2 from the paper showing internal meta-analyses of the design effect on estimated ATEs. The estimates consistently fall around 20% attenuation regardless of sample & design type (except within-subject designs on Prolific).

Figure 4 of the paper, showing how the design effect changes by how close repeated measures are placed together. The change is mostly flat as distance separating measures goes from 0 to 20 survey items.

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Andrew Trexler @atrexler.com · 24/04/2026

Our results: First, we find consistent evidence that RM designs attenuate ATE estimates by roughly ~20%. At the same time, PO designs are imprecise, requiring a large N for a reliable estimate. RM designs offer very large precision gains, by ~50% in our samples (note: N matters here).

Figure 5 from the paper, which shows histograms of the percentage change (from PO to RM) in the estimated ATE and standard error. The change in ATEs is clustered around 20% attenuations. The change in SEs is clustered around 50% reductions.

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Andrew Trexler @atrexler.com · 24/04/2026

What we do: 1. Partially replicate CSP with 6 studies each fielded on 3 distinct samples (18 studies, 13163 participants, 78978 total obs). 2. Increase evidence on within-subject designs 43-fold. 2. Compare probability & non-prob samples. 3. Randomize how close repeated measures appear together.

Table 1 from the paper, summarizing each study's design, treatment, and control arms.

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Andrew Trexler @atrexler.com · 24/04/2026

Scholars often prefer PO designs out of concern that pre-treatment measures may bias the estimate of the average treatment effect (via consistency pressures, priming, or demand effects). Clifford, Sheagley, & Piston (2021) provide evidence that these concerns are unwarranted: doi.org/10.1017/S000...

doi.org

Increasing Precision without Altering Treatment Effects: Repeated Measures Designs in Survey Experiments | American Political Science Review | Cambridge Core

Increasing Precision without Altering Treatment Effects: Repeated Measures Designs in Survey Experiments - Volume 115 Issue 3

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Andrew Trexler @atrexler.com · 24/04/2026

Background: classic post-only experiments randomize & deliver treatment, then measure outcomes only post-treatment. Repeated measure designs measure the outcome both pre- and post-treatment. (Within-subject variants deliver multiple treatments & measure outcomes multiple times.)

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Andrew Trexler @atrexler.com · 24/04/2026

First, a quick preview of the findings: 1. Repeated measure designs attenuate ATE estimates by ~20% on avg relative to classic post-only measurement. 2. RM designs also provide massive gains in statistical power. 3. For most applications, power gains will trump ATE attenuation, so use RM designs.

Figure 3 of the paper. The figure displays the estimated ATE of each experiment under each design (bootstrapped). The point estimates for the repeated measure design are nearly all attenuated relative to the post-only design, but the confidence intervals are also much smaller.

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Andrew Trexler @atrexler.com · 24/04/2026

Thrilled to announce my paper with @dianamejordan.bsky.social & sky-less Trent Ollerenshaw is now published open-access at @apsrjournal.bsky.social. In a (very) large replication & extension, we show that design effects of repeated measure experiments are nonzero but typically small. Thread:

Abstract for "New Evidence and Design Considerations for Repeated Measure Experiments in Survey Research" by Diana Jordan, Trent Ollerenshaw, and Andrew Trexler, published in the American Political Science Review. The abstract text reads: "We re-examine recent influential claims that repeated measure experimental designs offer large precision gains without biasing treatment effect estimates in survey research. We test these claims by experimentally varying the design of six classic political science experiments across three distinct large samples of U.S. adults (total N = 13,163). In contrast to prior evidence, we observe consistent attenuation of treatment effects in repeated measure designs. However, we show in simulations that this average design effect is small enough, and the precision gains large enough, that we recommend repeated measure designs for broad application—though (large-N) post-only designs may be preferable when research priorities include estimating the precise magnitude of a treatment effect. We additionally explore how several design considerations affect the bias-precision trade-off, such as within-subject versus between-groups designs, the relative separation of repeated measures within single surveys, and differences in respondent characteristics across sample types."

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British Journal of Political Science @bjpols.bsky.social · 08/04/2026

From February 2026 - The Unequal Challenge of Learning from Under-Informative News - cup.org/461vHAT "findings shed light on the importance of considering heterogeneous preferences along ethnicities within the same racial ‘in-group’" - @atrexler.com #OpenAccess

BJPolS abstract discussing political news consumption. It highlights the dependency of outlets on audience preferences, with coverage focusing on partisan conflict and specialized jargon.

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Jon Green @jongreen.bsky.social · 03/04/2026

extremely happy to share that "Political Pundits and the Maintenance of Ideological Coalitions" is conditionally accepted at @polbehavior.bsky.social osf.io/8c3fr/files/...

Title: Political Pundits and the Maintenance of Ideological Coalitions
Authors: Allison Wan and Jon Green
Abstract: Political ideologies help groups advance diverse sets of interests under common agendas. However, it is unclear how these groups maintain their norms regarding what it means to be
a member in good standing in a dynamic information environment. Building on theories of “long” political coalitions, we hypothesize that ideological elites’ rhetorical influence on one another will tend to be concentrated and specialized with respect to specific concepts. We
find support for this expectation using an original dataset of over 1,000 prominent political pundits in the United States, in which we infer coalition membership and the diffusion of novel language over a range of specific concepts. While pundits may discuss many concepts,
they tend to “send” language to other pundits in relatively few, resulting in both concentration and specialization of influence within coalitions. These results clarify conceptual distinctions between political ideologies and political philosophies, and demonstrate real-time dynamics of contemporary ideological coalitions.

Figure 1: Stylized expectations. Each node reflects a hypothetical coalition member, colors denote concepts, and arrows indicate members’ influence on each other. For example, member (a) influences members (b), (c), and (e) with respect to one concept, such as immigration, while member (d) influences members (b), (c), and (e) with respect to a different concept, such as health care. Member (e) acts as a broker, both sending and receiving influence across the coalition. Every member is influential, but influence tends to be concentrated (for any given concept, one member accounts for 3/4 of influence) and specialized (4/5 members are influential on only one concept).

Figure 3: Concentration of influence within concepts, observed network compared to permuted networks. Degree, Community, and Concept denote structural features either are or are not preserved in network permutations.

Figure 4: Specialization of influence within concepts, observed network compared to permuted networks. Degree, Community, and Concept denote structural features either are or are not preserved in network permutations.

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Erika Franklin Fowler @efranklinfowler.bsky.social · 05/03/2026

We’re hiring — help us spread the word! @tnridout.bsky.social @mikefranz.bsky.social

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APSA & ICA Political Communication Divisions @polcomm.bsky.social · 09/02/2026

The APSA Political Communication section is accepting nominations for its annual awards. Please send nominations directly to the chair of each committee. 🔎 More details on awards, committee, and eligibility criteria: politicalcommunication.org/awards/

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