Women legislators face a variety of gendered barriers both outside and inside the legislature. Yet, little previous scholarship has quantitatively examined whether legislative insiders are biased against women and their accomplishments. We explore a new potential explanation for gender inequity in legislatures: that women in office may get less credit than men for similar achievements. If legislative insiders systematically undervalue women’s work, women will have a harder time gaining influence within the chamber; alternatively, those working in and with the legislature may be uniquely aware of the effort that goes into representational activities and can observe the work that women perform firsthand. To examine this question, we combine elite evaluations of legislators from the North Carolina General Assembly with data on committee assignments, legislative effectiveness, electoral performance, and more. We find little systematic evidence that women legislators’ accomplishments are valued less than those of the men with whom they serve.

Objectives/Goals: Transmission-blocking vaccines hold promise for malaria elimination by reducing community transmission. But a major challenge that limits the development of efficacious vaccines is the vast parasite’s genetic diversity. This work aims to assess the genetic diversity of the Pfs25 vaccine candidate in complex infections across African countries. Methods/Study Population: We employed next-generation amplicon deep sequencing to identify nonsynonymous single nucleotide polymorphisms (SNPs) in 194 Plasmodium falciparum samples from four endemic African countries: Senegal, Tanzania, Ghana, and Burkina Faso. The individuals aged between 1 and 74 years, but most of them ranged from 1 to 19 years, and all presented symptomatic P. falciparum infection. The genome amplicon sequencing was analyzed using Geneious software and P. falciparum 3D7 as a reference. The SPNs were called with a minimum coverage of 500bp, and for this work, we used a very sensitive threshold of 1% variant frequency to determine the frequency of SNPs. The identified SNPs were threaded to the crystal structure of the Pfs25 protein, which allowed us to predict the impact of the novel SNP in the protein or antibody binding. Results/Anticipated Results: We identified 26 SNPs including 24 novel variants, and assessed their population prevalence and variant frequency in complex infections. Notably, five variants were detected in multiple samples (L63V, V143I, S39G, L63P, and E59G), while the remaining 21 were rare variants found in individual samples. Analysis of country-specific prevalence showed varying proportions of mutant alleles, with Ghana exhibiting the highest prevalence (44.6%), followed by Tanzania (12%), Senegal (11.8%), and Burkina Faso (2.7%). Moreover, we categorized SNPs based on their frequency, identifying dominant variants (>25%), and rare variants (Discussion/Significance of Impact: We identified additional SNPs in the Pfs25 gene beyond those previously reported. However, the majority of these newly discovered display low variant frequency and population prevalence. Further research exploring the functional implications of these variations will be important to elucidate their role in malaria transmission.

How do term limits affect dyadic ideological representation? Despite reformers’ claims that term limits should improve legislators’ connections to their constituents, much empirical political science research suggests that term limits actually break that electoral connection. In this study, I use a regression discontinuity design to measure the ideological gap in how Democrats and Republicans represent evenly matched districts and then explore how this gap varies across settings with and without state legislative term limits in effect. Across a number of specifications, my results are consistent with term limits exacerbating rather than improving dyadic representation. This study contributes to a growing scholarly consensus that term limits do not improve, and may worsen, state legislative representation.

Do constituents care how judges are chosen? We conduct two nationally representative survey experiments focusing on state trial courts. Our first study indicates that respondents prefer judges who are elected to those who are appointed, though this does not affect their perceptions of the judiciary’s legitimacy. Our second study explores three potential mechanisms: efficacy, experience with democracy, and perceived ideological proximity. We find evidence that real-world experience with judicial elections is associated with a preference for such elections, but we do not find evidence for other mechanisms. Our study offers important new evidence for assessing proposed reforms to judicial selection.

De Neys argues against assigning exclusive capacities to automatic versus controlled processes. The dual implicit process model provides a theoretical rationale for the exclusivity of automatic threat processing, and corresponding data provide empirical evidence of such exclusivity. De Neys's dismissal of exclusivity is premature and based on a limited sampling of psychological research.

Significant parts of the archaeological record are in private hands, including those of responsible and responsive stewards (RRS). This is not necessarily a bad thing. The Central Ohio Archaeological Digitization Survey (COADS) engages RRS in collaborative study of central Ohio prehistory. COADS leverages the mass of RRS data constructively to add depth and breadth to a regional archaeological record. We recorded over 12,000 diagnostic points and about 5,000 other stone tools from 32 RRS collections. All were scanned as two-dimensional (2D) images, and a sample as three-dimensional (3D) models for landmark-based geometric morphometric (LGM) analysis and GIS analysis of prehistoric land use. The resulting dataset is >4.7 times the number of diagnostics recorded in the Ohio SHPO database for the region, shedding new light on land use and tool use over millennia. In addition to academic research, COADS creates an accessible collection of 3D models available to RRS colleagues and to society at large. This reciprocal sharing mutually benefits professionals and the RRS community. Professionals are not the only ones who research the cultural past; the more and better we collaborate with RRS and others with legitimate interests, the better our common understanding of that past.

Quasi-periodic plasmoid formation at the tip of magnetic streamer structures is observed to occur in experiments on the Big Red Ball as well as in simulations of these experiments performed with the extended magnetohydrodynamics code, NIMROD. This plasmoid formation is found to occur on a characteristic time scale dependent on pressure gradients and magnetic curvature in both experiment and simulation. Single mode, or laminar, plasmoids exist when the pressure gradient is modest, but give way to turbulent plasmoid ejection when the system drive is higher, which produces plasmoids of many sizes. However, a critical pressure gradient is also observed, below which plasmoids are never formed. A simple heuristic model of this plasmoid formation process is presented and suggested to be a consequence of a dynamic loss of equilibrium in the high-$\beta$ region of the helmet streamer. This model is capable of explaining the periodicity of plasmoids observed in the experiment and simulations, and produces plasmoid periods of 90 minutes when applied to two-dimensional models of solar streamers with a height of $3R_\odot$. This is consistent with the location and frequency at which periodic plasma blobs have been observed to form by Large Angle and Spectrometric Coronograph and Sun Earth Connection Coronal and Heliospheric Investigation instruments.

Analyzing variation in treatment effects across subsets of the population is an important way for social scientists to evaluate theoretical arguments. A common strategy in assessing such treatment effect heterogeneity is to include a multiplicative interaction term between the treatment and a hypothesized effect modifier in a regression model. Unfortunately, this approach can result in biased inferences due to unmodeled interactions between the effect modifier and other covariates, and including these interactions can lead to unstable estimates due to overfitting. In this paper, we explore the usefulness of machine learning algorithms for stabilizing these estimates and show how many off-the-shelf adaptive methods lead to two forms of bias: direct and indirect regularization bias. To overcome these issues, we use a post-double selection approach that utilizes several lasso estimators to select the interactions to include in the final model. We extend this approach to estimate uncertainty for both interaction and marginal effects. Simulation evidence shows that this approach has better performance than competing methods, even when the number of covariates is large. We show in two empirical examples that the choice of method leads to dramatically different conclusions about effect heterogeneity.

Magnetic reconnection is explored on the Terrestrial Reconnection Experiment (TREX) for asymmetric inflow conditions and in a configuration where the absolute rate of reconnection is set by an external drive. Magnetic pileup enhances the upstream magnetic field of the high-density inflow, leading to an increased upstream Alfvén speed and helping to lower the normalized reconnection rate to values expected from theoretical consideration. In addition, a shock interface between the far upstream supersonic plasma inflow and the region of magnetic flux pileup is observed, important to the overall force balance of the system, thereby demonstrating the role of shock formation for configurations including a supersonically driven inflow. Despite the specialized geometry where a strong reconnection drive is applied from only one side of the reconnection layer, previous numerical and theoretical results remain robust and are shown to accurately predict the normalized rate of reconnection for the range of system sizes considered. This experimental rate of reconnection is dependent on system size, reaching values as high as 0.8 at the smallest normalized system size applied.