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The gap between women's representation in the Democratic and Republican parties has grown significantly in the last three decades. We argue existing explanations undervalue voters' contributions to this trend by focusing on voter responses to candidate sex rather than candidate gender. We theorize that Republican voters (especially the most conservative) prefer masculine candidates in intraparty and entry-level elections. Because sex and gender are correlated, this limits the number of Republican women who advance through the political pipeline. Experimental vignettes from two rounds of the Cooperative Congressional Election Study (N  = 2,000) and two large surveys of Republicans (N  > 10,000) show that Republican (but not Democratic) voters penalize candidates with "feminine" self-presentation regardless of the candidate's sex. Original data on the self-presentation of Republican candidates for entry-level office (N  = 459) confirm Republican candidates often present themselves in gender-stereotypical ways. In short, voters play an underappreciated role in the partisan gap in women's representation. [ABSTRACT FROM AUTHOR]

A growing body of research indicates that voters' perceptions of the electoral system change when the means of administering elections change. As some electoral jurisdictions have moved to systems designed to increase voter convenience, little is known about whether convenience is achieved at the expense of confidence. Utah's rollout of Vote by Mail (VBM) occurred county by county across five federal elections, and the three most populous counties adopted all VBM elections successively in 2014, 2016, and 2018. This meaningful variance in voter experience with VBM allows us to model the relationship between experience with VBM and voter confidence. We find that the switch to a more convenient system of voting came at the expense of diminished confidence in the voting process. However, experience with VBM is positively related to confidence such that the loss in confidence can be recouped over time. To capture this dynamic relative to other factors, we also estimate the effects of partisanship and the messages of political elites. In the aftermath of the 2020 election, the effect of partisanship on voter confidence changed compared to just two years earlier. Elite messages appear to be especially negative for Trump voters after 2020. More experience with VBM acts as a bulwark against those negative messages, almost completely attenuating the negative effects of Trump's fraud claims among his voters with the highest levels of VBM experience. [ABSTRACT FROM AUTHOR]

Despite consensus regarding the civic shortcomings of American citizens, no such scholarly consensus exists regarding the effectiveness of civic education addressing political apathy and ignorance. Accordingly, we report the results of a detailed study of students enrolled in introductory American politics courses on the campuses of two large research universities. The study provides pre- and postmeasures for a broad range of political attitudes and behaviors and includes additional long-term observations in survey waves fielded 6, 12, and 18 months after the conclusion of the class. Long-term observation provides leverage absent in many prior studies and enables us to compare the changes we observe during the semester to those that take place beyond the confines of the classroom and during important political events, such as the 2012 presidential election. Also embedded in the study is an experiment designed to assess whether students' enthusiasm for "new media" (e.g., blogs) can be harnessed in American politics courses to stimulate long-lasting political engagement. We find evidence that civic education matters for some, but not all, measures of political engagement. Moreover, we find evidence that what one does in the classroom also matters. For some dimensions of political engagement, this study finds evidence of lasting civic education effects and the experimental manipulation compellingly locates the source of some engagement variation in the classroom.

Data-driven medium-range weather forecasts have recently outperformed classical numerical weather prediction models, with Pangu-Weather (PGW) being the first breakthrough model to achieve this. The Transformer-based PGW introduced novel architectural components including the three-dimensional attention mechanism (3D Transformer) in the Transformer blocks. Additionally, it features an Earth-specific positional bias term which accounts for weather states being related to the absolute position on Earth. However, the effectiveness of different architectural components is not yet well understood. Here, we reproduce the 24 h forecast model of PGW based on subsampled 6-hourly data. We then present an ablation study of PGW to better understand the sensitivity to the model architecture and training procedure. We find that using a two-dimensional attention mechanism (2D Transformer) yields a model that is more robust to training, converges faster, and produces better forecasts compared to using the 3D Transformer. The 2D Transformer reduces the overall computational requirements by 20 %–30 %. Further, the Earth-specific positional bias term can be replaced with a relative bias, reducing the model size by nearly 40 %. A sensitivity study comparing the convergence of the PGW model and the 2D-Transformer model shows large batch effects; however, the 2D-Transformer model is more robust to such effects. Lastly, we propose a new training procedure that increases the speed of convergence for the 2D-Transformer model by 30 % without any further hyperparameter tuning.

Abstract Using ex vivo microscopy, virtual pathology can improve histological procedures by providing pathology images in near real-time without tissue destruction. Several emerging and promising approaches leverage fast-acting small-molecule fluorescent stains to replicate traditional pathology structural contrast, combined with rapid optical sectioning microscopes. However, several vital challenges must be addressed to translate virtual pathology into the clinical environment. One such challenge is selecting robust, reliable, and repeatable staining protocols that can be adopted across institutions. In this work, we addressed the effects of dye selection and staining protocol on image quality in rapid point-of-care imaging settings. For this purpose, we used structured illumination microscopy to evaluate fluorescent dyes currently used in the field of ex vivo virtual pathology, in particular, studying the effects of staining protocol and temporal and photostability on image quality. We observed that DRAQ5 and SYBR gold provide higher image quality than TO-PRO3 and RedDot1 in the nuclear channel and Eosin Y515 in the extracellular/cytoplasmic channel than Atto488. Further, we found that TO-PRO3 and Eosin Y515 are less photostable than other dyes. Finally, we identify the optimal staining protocol for each dye and demonstrate pan-species generalizability.