Michael Jankowski
@michaelj505
It's not a peak, it's a plateau | Manager @ PwC | PhD in Political Science | Interested in Chess & Badminton
977Followers
117Following
358Posts total
411.4KViews on collected posts
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@michaelj505 Showing that something we though was supported by data in fact is not supported by data does not significantly advance scholarly debate? Then what does?
1.1K views · 15 likes
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Here is our full replication report: https://t.co/l9eJj3q8jT
The response of the authors: https://t.co/7G0T1QXr5Z
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It was a pleasure to collaborate with @Ben_Guinaudeau on the project, and we are very grateful to the Institute for Replication (@I4Replication) for providing a platform structuring these difficult and nonetheless important exchanges between authors and replicators.
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Arguing that small-n studies are known to be sensitive to outliers does not convince me. Neither the authors nor the papers citing the study discuss the limitations arising from small-n studies. The severe sensitivity of the results is not publicly known and deserve awareness.
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Writing replications which contradict the original findings is no fun task, but it is nonetheless an essential part of academic publishing, especially when the topic matters that much.
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However, the APSR started an investigation which lasted until December ’22 and concluded that no corrigendum is necessary. This decision was based on an undisclosed response from the authors and a single reviewer report, summarized by the APSR as described in the picture below. h
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I must admit that APSR’s arguments were not very convincing. To provide code that accurately reproduces the article’s results is a good signal, but it is far from representing a reasonable benchmark when assessing the robustness of a paper.
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The APSR desk rejected the letter as “it primarily serves to correct the record by identifying issues that call into question the reliability of the findings […and…] does not significantly advance scholarly debate about the substantive or methodological issues at stake”.
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The circumstances under which Maréchal-Le Pen was elected also question the relevance of the case. Maréchal-Le Pen was only elected by a relative majority, because the PS candidate refused to withdraw from the race in the second round, against the advice of the party leadership.
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If Marechal-Le Pen was not elected in 2012, which would have been likely if the PS candidate withdrew from the second round, the value of the dependent variable would drop from 50% to 0% which radically changes the results.
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An in-depth analysis of the case, thus, reveals that the observation of Front National in 2012 is not particularly suitable to support the theoretical mechanism: Essentially, the main result of the paper is contingent on the election Marechal-Le Pen.
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While technically correct, it is important to note that Front National in 2012 only elected two legislators, of which one was female (Marion Maréchal-Le Pen, the niece of Marine Le Pen). Front National did not elect more women; they elected a single woman. https://t.co/YEKkJu6nIk
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Moreover, Front National also had a very large value in the dependent variable (share of elected female candidates). In fact, with 50% of the elected candidates being female, it has the highest value of all 58 cases.
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Therefore, the values of Front National in 2012 in the independent and dependent variables perfectly align with WMKC’s hypothesis. The problem is, however, that the value of 50% in the dependent variable is somewhat misleading.
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Front National in 2012 also lost votes in the previous election. Thus, the party was in the exact situation for which WMKC’s argument expects an increase in the number of elected female politicians.
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At first glance, the observation is a perfect example for the theoretical mechanism. Front National in 2012 had a large lagged male-to-female voter ratio, which is used for measuring a predominance of male voters in the previous election.
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One might argue that Front National in 2012 needs to be included because it is such an informative case for the analysis. There is no doubt that Front National is a very prominent example of a PRRP in Europe. But what makes this observation so impactful?
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This is quite a drastic change in the regression estimates and it strongly affects the conclusions drawn from the statistical analysis. The inclusion of a single observation has a massive effect on whether we reject the null hypothesis of no effect.
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This raises the question: Why does the Front National in 2012 have such a strong effect? This question is less trivial than it seems.
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The effect is gone. In the most favorable model specification, the coefficient of the interaction effect changes from -0.87 (p < 0.01) in the published paper to -0.15 (p = 0.71) in the replication. In other specifications, the interaction equals zero with a p-value > 0.99. https:
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We then evaluated how the results are affected by excluding this observation. We ran the regression models without it and display how the interaction effect changes compared to the published result. https://t.co/AIUvepPCKZ
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This analysis reveals that one observation, the Front National (now Rassemblement National) in the French Parliamentary Election of 2012, has a very strong effect on the regression coefficients.
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In our replication, we applied standard regression diagnostics to the regression models, including estimating Cook’s D, which measures how strongly each observation influences the regression coefficients. https://t.co/kj7rCNR0aZ
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However, the plot above is based on an interaction effect estimated from a sample of 58 cases. Small sample sizes can be challenging for empirical analysis as they have low power and results are more likely to be unduly influenced by individual outliers.
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We replicate the paper of Weeks, Meguid, Kittilson and Coffé (WMKC) on populist radical-right parties (PRRP) use of strategic descriptive representation. Based on this theory, PRRPs will elect more women when they've lost votes previously and have a predominantly male voter base.
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WMKC show a significant and substantial interaction effect which supports their hypothesis. The figure below depicts the main finding from the APSR paper. https://t.co/YHtmXNmGcH
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Is a study robust when its findings depend on the inclusion of a single observation?
In a new report, @Ben_Guinaudeau and I discuss this question based on the replication of an @apsrjournal article. A thread on our main findings.
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We have a new reproduction and response by the authors! The original article is entitled "When Do Männerparteien Elect Women? Radical Right Populist Parties and Strategic Descriptive Representation" (by Weeks et al.) The reproducers are Guinaudeau and Jankowski. https://t.co/gJ4
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Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
4.7K13 Sep
4.7K
5.1K
5K
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74.8K
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27K
4.4K
6.1K
4K
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Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.19%13 Sep
0.15%
0.29%
0.26%
0.25%
0.14%
0.11%
0.48%
0.11%
0.86%
0.48%
0.60%
0.82%
1.42%
Reactions — likes, reposts, replies and quotes — divided by views.
What the audience does
Likes67.5%615 in total
Reposts6.5%59 in total
Replies4.1%37 in total
Quotes3.0%27 in total
Bookmarks19.0%173 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
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