Academic Publishing Total Landscaping

The other day I saw a lot of people sharing a link to a new study in The Lancet. The paper in question is titled “Cognitive deficits in people who have recovered from COVID-19” (see, for example, this and this tweet that went viral). I have not read the study and I have no plans of doing so. However, what is worth mentioning is the fact that it is actually not published in The Lancet. It’s published by The Lancet in a journal called EClinicalMedicine.

Again, I have not read the study and I cannot say whether it is “strong enough” to be published in The Lancet (and a lot of bad research will most likely find a home in The Lancet), but I am sure the researchers would rather publish the paper in The Lancet than EClinicalMedicine if they could. Accordingly, I find the branding of journals like EClinicalMedicine misleading. The idea is relatively simple: Take the name of The Lancet, publish a lot of journals that are not The Lancet, use the brand to attract attention to the pseudo-The Lancet journals among researchers (more submissions, citations, etc.), and let the journals be part of the business model of the publisher (= profit).

The Lancet (the publisher) is – in addition to the The Lancet (the journal) – publishing the following journals: The Lancet Child & Adolescent Health, The Lancet Diabetes & Endocrinology, The Lancet Digital Health, The Lancet Gastroenterology & Hepatology, The Lancet Global Health, The Lancet Haematology, The Lancet Healthy Longevity, The Lancet HIV, The Lancet Infectious Diseases, The Lancet Microbe, The Lancet Neurology, The Lancet Oncology, The Lancet Planetary Health, The Lancet Psychiatry, The Lancet Public Health, The Lancet Regional Health – Americas, The Lancet Regional Health – Europe, The Lancet Regional Health – Western Pacific, The Lancet Respiratory Medicine, The Lancet Rheumatology, EBioMedicine, and EClinicalMedicine.

I don’t mind all of these journals and names and whatnot, but I am quite confident that most people unfamiliar with academic publishing will see nothing but The Lancet when they read about studies published in any of the journals above (including journalists).

This is just one example and I could have picked any other publisher. Nature (the publisher) got even more journals published under the Nature name than I want to mention here, from Nature Aging and Nature Africa to Nature Reviews Rheumatology and Nature Synthesis (take a look here for the full list).

Nature also publish other journals, such as Scientific Reports, that people often believe is Nature (because of the url, typesetting, etc.). I wrote a post the other day about a study published in Scientific Reports where I also saw people calling it a Nature study. This is the point. Researchers with a paper that would never end up in Nature can pay $1,990 and use the Nature brand to promote their paper. And of course, Science publishes the journal Science Advances (which, ironically, does little to advance science) with a publication fee of $4,500.

We are also seeing more of this within the social sciences. American Economic Review, for example, is now accompanied by American Economic Review: Insights. I had a quick look at the articles published in the latter journal, and it goes without saying that most (if any) of these papers would never get published in American Economic Review (for reasons related to the scientific quality or rather lack hereof).

To my knowledge there are no good examples from political science (yet), but maybe that can explain why we have seen more mediocre research ending up in American Political Science Review lately? (You know, the kind of research that can only be explained by drunk participants and/or drunk editors/reviewers.) Maybe what we need in political science is “APSR: Insights“? Well, I don’t know, and maybe it is all for the better that academic publishers and journals are slowly ruining the reputation of their journals altogether.

Hopefully, in the near future, we can care more about the quality of the work rather than the name of the journal. Until that happens, for the love of science, please refer to EClinicalMedicine and not The Lancet when you talk about a study that is published in the former.

PPEPE added to Party Facts

Our data on populist parties in European Parliament elections (PPEPE), from our article in the Electoral Studies, is now linked to the Party Facts. You can find it here.

Party Facts, for people not already familiar with this amazing resource, links several datasets on political parties to make it easier for researchers to work with such data. At the time of writing, Party Facts cover 5765 core parties from 224 countries.

This means that it is now possible to link our data to several other high-quality political datasets such as ParlGov, V-Party, CHES, etc. You can find an example in R showing how you can easily link our PPEPE data to ParlGov, the Manifesto Project and CHES here.

Resources with research writing advice

I was going through a few resources with some good advice on writing research papers. Might be of interest to some of you:

How to write a great research paper (Simon Peyton Jones from Microsoft gives seven suggestions for how to improve your research papers)
Ten simple rules for structuring papers (Table 1 in the paper gives a good summary of the ten “rules”)
Writing Empirical Articles: Transparency, Reproducibility, Clarity, and Memorability (some good advice on how to write good science, e.g. increasing the transparency)
Writing a scientific paper, step by painful step (I’m not a fan of some of the suggestions, such as organising p-values, but overall a lot of good advice)
Robert’s Rules:Suggestions for Writing (motivational piece, e.g. “Write fast, in multiple drafts”)
10 Tips on How to Write Less Badly (especially relevant for people starting in grad school)
How to construct a Nature summary paragraph (good example on how to write a summary paragraph)
Publication, Publication (Gary King on how to structure a publishable paper)
Writing Tips for Ph. D. Students (a must read)
Common Expositional Problems in Students’ Papers and Theses (great set of advice — including some detailed advice on details)
Doing a Literature Review (recommended reading if you are doing a literature review)
Managing Your Research Pipeline (practical advice on how to structure multiple papers)
Mathematical Writing (+100 pages subject-specific advice on mathematical writing)
Three Templates for Introductions to Political Science Articles (great templates for introductions)
Writing Guide (Daniel Simons’ recommendations – including a good revision worksheet)
Of Publishable Quality: Ideas for Political Science Seminar Papers (great paper on how to think about ideas for research projects)
Rookie Mistakes: Preemptive Comments on Graduate Student Empirical Research Manuscripts (another great paper on rookie mistakes in empirical papers)
How to Read (and Understand) a Social Science Journal Article (focus is on reading an article but also relevant for writing)

The political scientist as a blogger

Ten years ago, John Sides wrote a paper titled The Political Scientist as a Blogger. Despite the fact that the internet is not the same today as it was ten years ago, it is still an interesting read. Specifically, the paper made me think about why political scientists should (not) blog in 2020, why I don’t like most political science blogs today and why I continue to write blog posts.

It’s quite simple. You can blog for various reasons but I believe this point from the paper sums it up: “Despite the occasional frustration, blogging can be fun — in fact, this is probably the first and best reason to do it. Once blogging starts to feel like work, you are probably not long for the blogosphere.”

I agree with this statement. Especially as a consumer of political science blogs. In fact, it is the reason I don’t read The Monkey Cage anymore (the paywall is another good reason though). It used to be great (pre-Washington Post) but the average quality is low nowadays and reads more like university press releases for mediocre studies. The reason is that most contributions to the blog today are ‘blogging for impact’ (pretty much the opposite of fun). Specifically, the blog is primarily researchers using the platform to write up a few paragraphs on their new research (to increase the public outreach of their work). Write a paper, write a blog post and aim to put the ‘Monkey Cage’ hyperlink on your CV. That is the mindset. And it shows.

Noteworthy, this is not to say that there are not good political science blogs out there. For example, I really enjoy the new blog Broadstreet (a blog on historical political economy). See, for example, this post on the recent quantitative work on the Nazi extermination and concentration camps (with a focus on testing individual-level psychological theories, post-treatment bias and other relevant issues). However, it is the exception compared to what blogging looked like ten years ago.

I guess the reason is that there is no need to blog as a political scientist. Supply and demand and nobody cares. If you want to build up a profile/brand/identity as a political scientist, create a Twitter account and engage directly with the political science community. Share your work (e.g. using the #polisciresearch hashtag), retweet interesting takes, reply and discuss, follow people who share relevant observations and material. No need to blog.

Actually, blogging can be a huge waste of your time if you take the opportunity costs into account. However, there’s a lot of ways to waste time and blogging is a fun way to do it. I guess that most people blogging today are those who care the least about building a huge audience (again, Twitter is the place to be if you’re in that game). Interestingly, the more I expect a lot of people will read my blog, the less I enjoy it.

I used to share my blog posts on Twitter but I stopped doing that. The moment I share a blog post I begin to care about the metrics. The quantitative assessment of the quality. Do people like or/and retweet the post? What do people say? And that’s funny because I usually don’t care about such data (or, that’s a lie). For that reason, I found it better to ‘detach’ my blog from everything else and try to let it live in its own universe.

However, that’s not the same as I don’t have an audience. And part of that audience is made up by political scientists. There is a certain ‘pre-social media’ nostalgia related to blogging that I enjoy. I guess at least some of my readers share that longing for old school blogging. I believe most of my readers are familiar with RSS-readers and, for that reason, I don’t pay attention to whether there is a coherent theme in my blogging (i.e. a target audience). I blog about various topics (political science and non-political science related). I blog in Danish and English. I blog about personal and non-personal stuff. In sum, I don’t consider my blog a political science blog per se.

Also, another aspect I found useful in order to further ‘detach’ my blog from any metrics and considerations was to schedule each written post for some point in the (distant) future. I believe there are two advantages to this. First, when writing a blog post, I pay less attention to whether/when people will read it and what they will say when it is published. Second, I have noticed that it is great to have a few months to read a post again and maybe add a few extra considerations (or hyperlinks) if I stumble upon something interesting (for example, I added the hyperlink to the tweet by Paul Ford after having written the first draft of this post).

There are good reasons to blog as a political scientist, but these are most likely not reasons for early career researchers (or anybody else) to begin blogging. If you are a political scientist considering the blog format, I recommend you focus on your research and send your blog posts to the Monkey Cage. That’s my simple career advice when it comes to political science blogging. And that’s why I don’t read a lot of political science blogs these days.

Political science syllabi

Over the years I have saved various syllabi in a local folder. I decided to do some digital housekeeping the other day with the aim of getting rid of the folder. Instead, I found links to the syllabi online and deleted the folder (including the ones that I couldn’t find).

This is a overview I made for myself but I bring it here in case it might be helpful to others. I provide the name of the teacher in parenthesis.


Experimentation and Causal Inference (Thomas J. Leeper)
GOVT 83.21 / QSS 30.03: Experiments in Politics (Brendan Nyhan)
Experimental Methods in Political Science (Bethany Albertson and Mike Findley)
Experimental Design and Social Behavior (Rick Wilson)
Gov 2008 Experimental Political Science (Ryan Enos and Dustin Tingley)
G4068: Experimentation in the Social Sciences (Costas Panagopoulos)

Political psychology

Government 2749: Political Psychology and International Relations (J. D. Kertzer)
GOVT 30:Political Misinformation and Conspiracy Theories (Brendan Nyhan)
PSCI4221: Political Psychology (Pavel Bacovsky)
Political Psychology (Michael F. Meffert)

Parties and institutions

PSCI 3031: Political Parties & Interest Groups (Nancy Billica)

Political communication and media

Political Communication, Media and Public Policy (Rasmus K. Nielsen)
Political Communication and Media Effects (Michael F. Meffert)

European Union

PSCI 4302: Politics of the European Union (Joe Jupille)


Electoral Politics (Miguel R. Rueda)

Public opinion and political behaviour

Public Opinion & Political Communication (Daniel Flynn)
Voters, Public Opinion and Participation (Tom O’Grady)
Public opinion & political behavior (Jennifer Wolak)

Text as data

Psych/CSCI 626: Text as Data (Morteza Dehghani)
Quantitative Text Analysis (Stefan Müller)
Automated Text Analysis in Political Science (Martijn Schoonvelde)


Survey Design and Analysis (Carey E. Stapleton)
Course on Design and Analysis of Sample Surveys (Andrew Gelman)
Using Surveys for Research and Evaluation (Thomas J. Leeper)

Research design

PLSC508b: Dissertation Workshop: Research Design & Causal Inference (Chris Blattman)
Sociology 750 – Research Design and Practice in Sociology (Jeremy Freese)
Political Analysis (John Gerring)
Political Analysis: A Primer (John Gerring)
GV505 Research Design in Political Science (Simon Hix and Paul Mitchell)
Political Science 522 Research Design and Analysis in Quantitative Research (James H. Kuklinskiand and Jake Bowers)
PAD 6707 Logics of Inquiry (Rick Feiock)
POL580 Methods of Political Inquiry (William Mishler)
Causal Analysis in Data Science (Tom O’Grady)


Statistical Inference: Linear Models, Descriptive, Causal and Statistical Inference (Jake Bowers)
POS 5747 Special Topics in Advanced Quantitative Analysis: Causality, Matching, and Multilevel Models (Jason Barabas)
PUBL0050 Advanced Quantitative Methods (Jack Blumenau)
17.835: Machine Learning and Data Science in Politics (In Song Kim)
Machine Learning for Social Scientists (Rochelle Terman)
POL-GA 1251 Quantitative Political Analysis II (Cyrus Samii)
POS 5746 Advanced Quantitative Analysis in Political Science (Jason Barabas)
POS 3930 Advanced Research Methods in Political Science (Jason Barabas)
Dynamic Analysis (Time Series Modeling in Politics) (Jan Box-Steffensmeier, John R. Freeman & Jon Pevehouse)
Political Science 688: Applied Bayesian and Robust Statistical Methods in Political Research (Jake Bowers)
GOV 2003: Topics in Quantitative Methodology (Kosuke Imai & Santiago Olivella)
POL 245: Visualizing Data (Kosuke Imai)
POL345/SOC305: Introduction to Quantitative Social Science (Margaret Frye & Kosuke Ima)
POL 451: Statistical Methods in Political Science (Kosuke Imai)
Stat186/Gov2002: Causal Inference (Kosuke Imai)
Topics in Applied Econometrics (J. Angrist & W. Newey)
Introduction to Machine Learning (Justin Grimmer)
POLS 509: The Linear Model (Justin Esarey)
17.800: Quantitative Research Methods I (Teppei Yamamoto)
17.802: Quantitative Research Methods II (Teppei Yamamoto)
17.804: Quantitative Research Methods III (Teppei Yamamoto)
17.806: Quantitative Research Methods IV (In Song Kim)
Political Science 208: Political Science Methods (Justin Esarey)
Political Science 590: Matching for Adjustment and Causal Inference
GOVT 10: Quantitative Political Analysis
Political Science 2580: Introduction to Quantitative Research Methods (Paul Testa and Marie Schenk)
Time Series Analysis (Jamie Monogan)


Mathematics for Political and Social Research (i.e., Extended Math Camp) (David A. Siege)
Mathematical Tools for Political Scientists (Miguel R. Rueda)


Repository of syllabi on experiments from a variety of social scientists

Word limits in political science journals

Different political science journals have different article formats with different word/page limits. Consequently, whenever you want to submit an article to a journal, the first thing to look up is the exact word limit.

In order to get a sense of the different article formats and word limits in political science journals, I have created an overview. The overview shows word limits for long articles, short articles and review essays/articles.

The overview currently consists of 65 journals and I will most likely add more journals (and more features) in the future. Do reach out on Twitter or drop me a mail if you got any feedback or if there is a specific journal of relevance to political scientists that I should add to the overview.

Last, the overview is sorted by impact factor (obtained with the excellent scholar package in R).