-->PONE-D-25-07395-->-->Registered report: Stress testing predictive models of ideological prejudice-->-->PLOS ONE

Dear Dr. Thompson,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

 -->-->As you will find in the reviewer comments, both reviewers find merit in the research presented and both agree that the data may provide a useful contribution to the existing literature. However, both reviewers have concerns that we would like to see addressed in a final version of the paper. Because you have already published a Registered Report Protocol, you will likely need to address these comments to the best of your ability in the Discussion of your paper. Note that Reviewer 1 defers to me in a comment regarding the use of p values in addition to model fit. I recommend that you defer to the planned analyses as indicated in your published protocol (which includes the use of p values). Please feel free to reach out to me if you have any questions regarding the comments; I know it can get tricky when aspects of the paper are already published. 

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PLOS ONE

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1. Does the manuscript adhere to the experimental procedures and analyses described in the Registered Report Protocol?

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Partly

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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-->6. Review Comments to the Author

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Reviewer #1: This was a paper extending some previous work building predictive models of prejudice toward various groups. I very much support iterative progression of these more formal modeling approaches, and I thought the adaptation to relative differences, another very common operationalization of prejudice in the field, was an important extension. Generally the authors find additional support for the ideology model over some other specifications. Thoughts and concerns follow:

Major concerns:

Because this paper is basically extending the Brandt 2017 model, some of these questions and critiques necessarily apply to that work as well. It's a little odd because that work is published and established, but still think it makes sense for the authors to engage with some of the questions in the present work.

-One thing I've always wondered with these models is about construct validity, or how much this "rating of ideology" is capturing the same or similar latent construct of prejudice. On their face, certainly distinct to me. But to the extent this variable is capturing "the extent to which i see these various groups on my team or not", it's less surprising to find such a strong link with how much I like those groups.

-A related concern is that these models depend on ratings on a bipolar liberal to conservative scale. Such a scale would just not work in the majority of countries in the world in which the political spectrum can't be reduced to one dimension. If our goal is purely non-explanation based prediction in the US, that's totally fine of course. But makes it more challenging to argue this is a causal model of the more universal force of prejudice, or it would have to be tweaked in some way. I guess this critique hinges on how the authors are interpreting this model, and I'd like to see that spelled out.

I've grouped these two together because they have perhaps been engaged with by the authors elsewhere, and I think could be handled here by some mention in the General Discussion.

-Regarding the modeling, I found the use of demographic controls conceptually problematic. If the goal is to predict prejudice from ideology, status, choice, and anything else, why should these be adjusted for the demographics of the participant? To adjust for gender, for example, is to say that men are just inherently more prejudiced toward xyz groups in a way that can't be explained or captured by other psychological variables, and I just don't believe that to be true. Plus it changes the very spare model (ideology) to be a lot more conceptually clunky, like who knows what other psychological baggage is being captured by "man" and "educated", but my guess is quite a bit. How much are results contingent on the inclusion of these demographic controls?

-My largest and perhaps controversial philosophical concern was the use of null hypothesis testing for model selection, and looking at p-values as evidence. I just didn't find it appropriate for the goals here. Models with the lowest average MSE simply fit the data best, regardless of whether they fit "significantly" better than other models with higher MSEs. Data science world would focus only on model fit, and this feels like a psych/data science mashup, employing both frameworks for evidence simultaneously. I'd defer to the editor, but I wouldn't be averse to cutting the p-value framework from the paper entirely, and relying only on model fit to determine the best models (and it would result in an identical conclusion from the line already being walked in the general discussion).

-What is an "ideologically relevant group" exactly? There needs to be a clear definition for this, rather than just sounds ideologically relevant to the authors and readers. I'm sympathetic in some respects, yes, those groups certainly seem ideologically relevant. But some of the groups not included in this bundle also seem ideologically relevant, and when I start squinting, many of these groups seem like they could also be ideologically relevant. A clear definition would sort this out, especially because the authors tenatively posit on page 25 that prediction success is better for these groups. Without some explanation, feel this risks being a "just so" story.

-On page 29, the authors mention they combined explicit and reaction time measures. What does this mean? How were they combined. Some folks consider implicit vs. explicit measures of prejudice quite distinct, so this feels odd.

Minor concerns:

-Intro of 2nd para- the prejudice literature has offered far more than just 3 predictors of prejudice. Maybe can revise this sentence to suggest Brandt identified three in his models. The entire field has prob put out at least 50.

-A line in the General Discussion mentions this is the "first time" predictive models were built for relative prejudice. While this is possibly true for the Brandt ideological prejudice models, it's not in general. Hehman & Neel psych review recently had some predictive models of prejudice with relative measures (and non-relative measures, a nice parallel to the current work and Brandt 2017). In general, I don't always find lines in papers noting "first" are so important, since that's somewhat obviated as the point of the paper, and could just be adjusted or trimmed.

-Lot of measures, would be great to have a correlation table between everything somewhere, apologies if I missed this.

I appreciate the opportunity to review this interesting work.

Reviewer #2: This paper presents a “stress test” of models for predicting the ideology-prejudice association, comparing models that incorporate the perceived ideology, status, and choice in group membership of various target groups. I have focused this review on the results, conclusions, and adherence to the initial registered report protocol, given that the methods and research question have been reviewed previously. Overall, the manuscript adheres to the procedures and analyses described in the protocol, and exploratory analyses are clearly marked. The authors were careful not to place too much weight on exploratory analyses relative to pre-planned analyses. However, my main concern with the manuscript is that the results of one of the exploratory analyses drastically alter the overall conclusions that I believe can be drawn from the manuscript. Despite this analysis not being pre-planned, I believe the changes to the results are sufficiently large that the authors should temper their conclusions in the paper to take them into account. I expand on this point below. If the conclusions and discussion can be revised to better incorporate the results of this analysis, I believe this manuscript will be well-suited for publication and provide an important contribution to the literature.

In my reading, the exploratory analysis reported on page 25 very significantly alters the results and warranted conclusions of the paper. The authors find that when they exclude targets groups that are defined by ideology (e.g., Democrats and Republicans), there are no differences among the predictiveness of the various models (including the null model). This seems highly significant to me because the claim that perceived ideology predicts prejudice is only theoretically meaningful or interesting insofar as it is about groups not explicitly defined by ideology. It seems trivial to say that the biggest predictor of how much Republicans like Democrats (and vice versa) is their perceived ideology – in fact these seem more like control groups than target groups to me. The results of the exploratory analysis indicate that the advantage of the ideology models over the status, choice, and null models is solely due to the inclusion of these groups that are explicitly defined by ideology. However, the authors’ discussion, conclusion, and abstract still make strong statements about the benefit of the ideology model(s) over the other models, which I believe are unwarranted given these results. I believe these conclusions and interpretations should be revised to reflect the fact that ideology provides no better prediction than the other models for the groups that are not defined only by ideology.

On a separate note, the logic of the analyses was not always intuitive, and I believe in some places could benefit from additional examples or explanation. At the top of page 20, for example, the authors discuss calculating a predicted ideology-prejudice association for the group “Black people”. Here, it would be very helpful to walk the reader through what each of the values represents – what does the final estimate of -0.49 in this context mean? Further, the authors at times refer to predicting prejudice and at other times to the ideology-prejudice association, and I think this distinction could be clarified and highlighted more. As I understand, the main purpose of the study is to predict the association between ideology and prejudice; however, on page 20, for example, the authors seem to be working with actual prejudice values rather than associations (“we subtracted the actual ratings of prejudice across groups from the estimates from the equations, squared these values, and then found the average”). Additional explanation would be helpful here – why are actual prejudice values rather than associations being predicted here? Finally, at times the distinction between the participant’s ideology and the perceived ideology of the group became confusing, and I would encourage the authors to explicitly state which of the two they are referring to when they use the word “ideology” in order to reduce cognitive load for the reader.

Below are a few additional minor questions:

1. Could the authors expand on the choice to use mean squared error as a metric to compare models, rather than a metric that takes into account the number of parameters included in the model?

2. Were all the demographic control variables in the models used to get the observed ideology-prejudice associations the same as the ones used by Brandt (2017) to get the predicted ones?

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Reviewer #1: No

Reviewer #2: No

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<div>PONE-D-25-07395R1-->-->Registered report: Stress testing predictive models of ideological prejudice-->-->PLOS ONE

Dear Dr. Thompson,

Thank you for your resubmission to PLOS ONE. I think you've done an excellent job addressing the reviewers' concerns, and I think your final manuscript will make a nice contribution to the journal and to the literature. Please consider your manuscript conditionally accepted (although I had to select 'minor revision' to solicit final edits). Once you submit a clean, unmasked version, I will formally accept the manuscript. (One pedantic side note: in a few places you reference "this data." Please correct to "these data" as "data" are plural; I shouldn't care, but I hound my Methods students about this point, so I felt compelled to note it here.)

You can ignore some of the boilerplate instructions below (e.g., a rebuttal letter), which pertain specifically to resubmissions. But please let me know if you have any questions or issues.

Please submit your revised manuscript by Oct 30 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:-->

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

-->If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols .

We look forward to receiving your revised manuscript.

Kind regards,

Corey Cook

Academic Editor

PLOS ONE

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Registered report: Stress testing predictive models of ideological prejudice

PONE-D-25-07395R2

Dear Dr. Thompson,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Corey Cook

Academic Editor

PLOS ONE