Lowest Rated Papers

Emilio Mármol-Sánchez, Bastian Fromm, Nikolay Oskolkov, Zoé Pochon, Marianne Dehasque, Morteza Aslanzadeh, Elif Bozlak, Katherine Brown, Tom van der Valk, Panagiotis Kalogeropoulos, J. Camilo Chacón-Duque, Inna Biryukova, Peter D. Heintzman, Cecilia Furugård, Valeri Plotnikov, Albert Protopopov, Björn Andersson, Erik Ersmark, Kevin J. Peterson, Marc R. Friedländer, Love Dalén

Cell·2025·1 citations

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Laae001

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Untitled Paper

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JLA (Jurnal Lingua Applicata)·2025

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How Election Rules Affect Who Wins

Justin Grimmer, Eitan Hersh

Journal of Legal Analysis·2024·13 citations

Abstract Contemporary election reforms that are purported to increase or decrease turnout tend to have negligible effects on election outcomes. We offer an analytical framework to explain why. Contrary to heated political rhetoric, election policies have small effects on outcomes because they tend to target small shares of the electorate, have a small effect on turnout, and/or affect voters who are relatively balanced in their partisanship. After developing this framework, we address how the findings bear on minority voting rights. We then show that countermobilization from political parties cannot explain the small effects of election laws. We explain that even when a state passes multiple policies at the same time, the reforms will still only have a marginal effect on turnout and an ambiguous effect on who wins. Finally, we explain what policies should raise alarm about affecting outcomes.

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Propaganda and Conflict: Evidence from the Rwandan Genocide *

David Yanagizawa-Drott

The Quarterly Journal of Economics·2014·435 citations

AbstractThis article investigates the role of mass media in times of conflict and state-sponsored mass violence against civilians. We use a unique village-level data set from the Rwandan genocide to estimate the impact of a popular radio station that encouraged violence against the Tutsi minority population. The results show that the broadcasts had a significant effect on participation in killings by both militia groups and ordinary civilians. An estimated 51,000 perpetrators, or approximately 10% of the overall violence, can be attributed to the station. The broadcasts increased militia violence not only directly by influencing behavior in villages with radio reception but also indirectly by increasing participation in neighboring villages. In fact, spillovers are estimated to have caused more militia violence than the direct effects. Thus, the article provides evidence that mass media can affect participation in violence directly due to exposure and indirectly due to social interactions.

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What Is the Relationship between Hate Radio and Violence? Rethinking Rwanda's “Radio Machete”

Scott Straus

Politics & Society·2007·108 citations

The importance of hate radio pervades commentary on the Rwandan genocide, and Rwanda has become a paradigmatic case of media sparking extreme violence. However, there exists little social scientific analysis of radio's impact on the onset of genocide and the mobilization of genocide participants. Through an analysis of exposure, timing, and content as well as interviews with perpetrators, the article refutes the conventional wisdom that broadcasts from the notorious radio station RTLM were a primary determinant of genocide. Instead, the article finds evidence of conditional media e fects, which take on significance only when situated in a broader context of violence.

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On the Role of Transformer Feed-Forward Layers in Nonlinear In-Context Learning

Haoyuan Sun, Ali Jadbabaie, Navid Azizan

arXiv·2025

Transformer-based models demonstrate a remarkable ability for in-context learning (ICL), where they can adapt to unseen tasks from a few prompt examples without parameter updates. Recent research has illuminated how Transformers perform ICL, showing that the optimal linear self-attention (LSA) mechanism can implement one step of gradient descent for linear least-squares objectives when trained on random linear regression tasks. Building on this, we investigate ICL for nonlinear function classes. We first prove that LSA is inherently incapable of outperforming linear predictors on nonlinear tasks, underscoring why prior solutions cannot readily extend to these problems. To overcome this limitation, we analyze a Transformer block consisting of LSA and feed-forward layers inspired by the gated linear units (GLU), which is a standard component of modern Transformers. We show that this block achieves nonlinear ICL by implementing one step of gradient descent on a polynomial kernel regression loss. Furthermore, our analysis reveals that the expressivity of a single block is inherently limited by its dimensions. We then show that a deep Transformer can overcome this bottleneck by distributing the computation of richer kernel functions across multiple blocks, performing block-coordinate descent in a high-dimensional feature space that a single block cannot represent. Our findings highlight that the feed-forward layers provide a crucial and scalable mechanism by which Transformers can express nonlinear representations for ICL.

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Lowest Rated Papers

Erratum to: Follow the (ISSUE) Leader? The Leader-Led Nexus Revisited

Insights into infectious diseases through ancient pathogen genomics

Follow the Leader?: How Voters Respond to Politicians’ Policies and Performance. By Gabriel S. Lenz. Chicago: University of Chicago Press, 2012. 344p. $90.00 cloth, $27.50 paper

Ancient RNA expression profiles from the extinct woolly mammoth

Laae001

Untitled Paper

How Election Rules Affect Who Wins

Propaganda and Conflict: Evidence from the Rwandan Genocide *

How Does Local TV News Change Viewers’ Attitudes? The Case of Sinclair Broadcasting

What Is the Relationship between Hate Radio and Violence? Rethinking Rwanda's “Radio Machete”

On the Role of Transformer Feed-Forward Layers in Nonlinear In-Context Learning

Throwing Like a Slayer: A Phenomenology of Gender Hybridity and Female Resilience in Buffy the Vampire Slayer