Blaming Across the Aisle: Political Contrasting and Blame Attribution in the Danish Parliament
Markus Lundsfryd Jensen, Rune Egeskov Trust, Kenneth Christian Enevoldsen, Sara Kolding
Aarhus University · Center for Humanities Computing
Published September 22, 2026 · on the feed September 23, 2026 · ▲ 11 · arXiv 2609.26346
The abstract
Political discourse is widely perceived to be growing more hostile, yet robust evidence remains scarce. This study examines blame attribution in the Danish Parliament from 1997 to 2026, combining a purpose-built classifier, BlameBERT (F1: 0.80), with multilevel statistical modeling. The classifier is constructed using an annotation-efficient pipeline for blame attribution in low-to-mid resource languages. The results reveal a banana-shaped trajectory, with blame declining until around 2016 before entering a significant and sustained increase in recent years (2019-2026). Government status consistently influenced blame attribution - an effect we term political contrasting - with opposition parties blaming substantially more than governing parties. This effect was moderated by ideology: The blame-dampening effect of governing was less pronounced among right-wing parties, and ideological extremity amplified blame more strongly on the right. In recent years, the interaction between political wing and ideological extremity intensified, suggesting an ideological hardening of the blame rhetoric concentrated on the right of the political spectrum. Taken together, these patterns suggest that the perceived rise in harsh political language reflects not merely a general rhetorical drift, but an ideologically asymmetric hardening of political discourse. A sensitivity analysis showed that the conclusions were robust to varying classification thresholds.
The Brief
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Transcript
Blaming Across the Aisle. Political Contrasting and Blame Attribution in the Danish Parliament. By Markus Lundsfryd Jensen and three others, from Aarhus University and the Center for Humanities Computing. Published on the twenty-second of September. Its code repository is public and real: about thirty-five source files.
Political discourse is widely seen as growing more hostile, yet solid evidence is scarce. This study looks at blame attribution in the Danish Parliament, from the late nineties through to two thousand and twenty-six. Its claim is that the rise in harsh political language is not just a general drift in rhetoric. It is a hardening that is ideologically asymmetric, concentrated on the right. That distinction matters for how the change is understood. A general drift would touch every party alike. An asymmetric hardening points to particular parts of the political spectrum.
The tool is a purpose-built classifier, BlameBERT, with an F1 of zero point eight, combined with multilevel statistical modelling. The classifier comes from an annotation-efficient pipeline for detecting blame in low-to-mid resource languages. Over time, blame follows a banana-shaped trajectory. It declines until around two thousand and sixteen, then enters a significant and sustained increase from two thousand and nineteen onward. So the popular sense of rising hostility is borne out for recent years, but the longer record is not a straight climb. For much of the period, blame was falling.
Government status consistently shapes blame. Opposition parties blame substantially more than governing parties, and the authors name this effect political contrasting. Ideology moderates it. Being in government dampens blame less among right-wing parties, and ideological extremity amplifies blame more strongly on the right. In recent years the interaction between political wing and ideological extremity has intensified. The authors read that as an ideological hardening of blame rhetoric, concentrated on the right of the political spectrum.
The evidence is from one parliament, the Danish one, measured through one classifier. A sensitivity analysis showed that the conclusions held across varying classification thresholds. That check matters because every measurement in the study passes through the classifier. If the patterns had depended on where the line between blame and no blame was drawn, they would say more about the tool than about the parliament.
The finding refines a common perception rather than simply confirming it. Blame has risen recently, but not evenly across the chamber. Where one sits relative to government, and how far from the centre, shapes how much one blames, and in recent years that pattern has sharpened on the right.
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Learn it by doing: make the calls the authors made, guess the result before you see it, and defend it in a viva graded on your own words. Chapter 1 is right here.
Chapter 1 🧩 · The problem
Everyone says politics has turned nastier. Proving it takes a way to read a parliament's worth of speeches.
You want to test the claim that politicians have grown more hostile. Danish parliament transcripts from 1997 to 2026 hold far too many sentences for anyone to read.
The road ahead
- 1 · The problem ~7 min To test whether Danish politicians blame more than before, you must find blame in millions of sentences that nobody can read or cheaply label.
- 2 · What came before ~3 min
- 3 · The key idea ~8 min Let an English zero-shot model label translated sentences cheaply, train a Danish classifier on those labels, then model each party's blame over time.
- 4 · Choose your own research ~3 min
- 5 · Build the method ~8 min Label a sample cheaply, train BlameBERT, classify every speech, model blame by party and time, then test the findings across thresholds.
- 6 · The experiment ~6 min You’ll guess: From 1997 to 2026, how did the rate of blame in the Danish Parliament change over time?
- 7 · The viva ~5 min Three questions from the examiners, answered in your own words. Win it for the paper’s trophy.
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