Kyle Marquardt

@kailmarkvart.bsky.social

Professor, @sampol.bsky.social; Project Manager, @vdeminstitute.bsky.social; Iowan; klmarquardt.com

I have read this Response to my Comment and have written a Rejoinder, showing three things: 1. The multiverse is many correlated tests. 2. The randomization inference is wrong. 3. The trichotomous moderator reaffirms my point. I also enumerate 7 misleading claims, now in print in the APSR.

A Rejoinder to ‘Still Instrumentally Inclusive’ (Turnbull-Dugarte & López Ortega)
Daniel de KadtCornell University, Department of Governmentdekadt@cornell.edu
2026-08-01
Abstract Turnbull-Dugarte and López Ortega’s “Still Instrumentally Inclusive” (the Response) answers my replication (the Comment) of their 2024 American Political Science Review paper (the Article) with, among other things, a multiverse of 2,970 analyses based on eighteen different weighting schemes, randomization inference, and a trichotomous moderator. As I show in this rejoinder, each is undermined by bona fide errors in their code, their writing, and their interpretation. First, the multiverse is just many correlated variants of the same test. This is in large part due to the weighting schemes which suffer multiple problems (some due to code errors, some intrinsic), and are largely correlated variations on one weighting scheme. Second, due to code errors the randomization inference compares a weighted statistic against an unweighted null and, in the two heterogeneity tests, permutes the interaction column rather than treatment assignment column. Every permutation p-value the Response reports is therefore computed against the wrong reference distribution; when they are recomputed correctly, two of the five it reports as significant are no longer so, and they are the two the Response emphasizes. Third, the trichotomous moderator is erroneously described as terciles, but it is in fact based on non-tercile cutpoints. The key subgroup effect reported in the Response thus rests on comparing just thirty high-weight control respondents against thirty-one high-weight treated respondents, and ends up reaffirming my original point that the heterogeneity in study 2 is with respect to weights, and not immigration sentiment as their theory predicts. I close by documenting seven claims in the Response that are untrue or misleading.
Cambridge University Press Political Science & IR@cambup-polsci.cambridge.org · last wk.

#OpenAccess from @apsrjournal.bsky.social - Still Instrumentally Inclusive - https://cup.org/4bhrhsp "Do individuals in Western democracies shift their views on LGBT+ inclusion when exposed to opposition from Muslim out-groups?" - @turnbulldugarte.com & @bertous.bsky.social #FirstView

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Some comparisons between today's tech sector and industrial SEOs in command economies under state socialism practically offer themselves: • bureaucratic targets with questionable economic value [see here] • soft budget constraint [see Kornai] • legitimization by value for the power of the state

A screenshot of the following text from this FT article [https://www.ft.com/content/cc03adda-7b56-4392-8f9a-e83a71a25ea1]

Some Amazon developers must be suffering whiplash about how they use AI. The technology group sets targets for most of its developers to use AI tools. This year it started monitoring consumption and posting usage figures on internal leader boards.
But after the FT wrote in May that some workers were automating non-essential tasks to improve their ranking, Amazon took the leader boards offline. “Please don’t use AI just for the sake of using AI,” Amazon senior vice-president Dave Treadwell told staff.
The shift was a sign of how employers are already changing how AI should be used and incentivised. As model providers switch from subscriptions to token-based billing, the cost of profligate usage is starting to hit home. Using leader boards and embedding token use in performance reviews is “a really stupid way to do anything”, Jacob Lauritzen, chief
Prof Mike Yearworth@mikeyearworth.bsky.social · 3w ago

“Please don’t use AI just for the sake of using AI,” Amazon senior vice-president Dave Treadwell told staff.” www.ft.com/content/cc03...

In the northern hemisphere, it’s time for a summer break. 🌞 Why not use the well-earned rest to catch up with your democracy reading list? Here are some tips of recent publications from the V-Dem community. Links to the latest books, policy briefs and journal articles in the thread 🧵👇 1(4)

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1 of Putin’s closest allies for decades has been another Leningrad KGB guy, Nikolay Patrushev. Russian political analyst Andrei Kolesnikov once described him as “the one allowed to explain and clarify Putin’s thoughts.” Interview with him yesterday in official state paper. Short 🧵w/ quotes. 1/6

rg.ru

How many Iranians support the Islamic Republic? In a new working paper, we answer this using a nationally representative survey of 2,000 adults in Iran—and the list experiment, a method for measuring sensitive attitudes.

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Congrats to Natalia Otrishchenko, Artem Kharchenko, and Valentyna Shevchenko, for winning the AAUS best article prize for their article “Ukrainian Researchers in a War Documentation Project: Intertwined Experiences and Methodologies”! (Article link in next post)

University of California Press@ucpress.bsky.social · 2mo ago

Communist and Post-Communist Studies @cpcs.bsky.social article "Ukrainian Researchers in a War Documentation Project: Intertwined Experiences and Methodologies" wins American Association for Ukrainian Studies' top article prize ukrainianstudies.org/aaus-announc...

New book on democracy. #OpenAccess Seven Myths about Democracy by Jørgen Møller & Svend-Erik Skaaning, Routledge taylorfrancis.com/books/oa-mon.... Challenges (full or partial) misunderstandings about the meaning, trajectory, causes, and consequences of democracy.

Seven Myths about Democracy | Jørgen Møller, Svend-Erik Skaaning | Tay

This timely book challenges seven widespread misconceptions about democracy that continue to shape public and academic debates about its past, present, and

taylorfrancis.com

Happy to share that my #rstats package for IRT/ideal point models, idealstan, is back on CRAN as v1.0! idealstan supports mixed outcomes, missing data, and time-varying methods (splines, AR(1), etc)--and latent regression \w new latent marginal effects. 😎 cran.r-project.org/web/packages...

idealstan: Robust Measurement with 'Stan'

Offers item-response theory (IRT) ideal-point measurement modeling for diverse distributions, missing data, and over-time variation. Full and approximate Bayesian sampling with 'Stan' (&lt;<a href="ht...

cran.r-project.org