Partisanship is the primary driver of voter decision-making in the United States. Partisans expect to prefer their party’s candidates’ issue stances and personal characteristics. Even when they learn negative information, motivated reasoning often keeps them from changing their candidate evaluations or vote choice. However, there is a “tipping point” at which partisans will update their priors and may vote against their preferred party’s candidate. This study seeks to determine whether voters are more likely to reach that tipping point when they see a woman in their party, and under what circumstances. We use a unique experimental design to vary a candidate’s gender, congruence with major elements of the party platform, and their participation in a scandal. We find that women are often evaluated more negatively and that subjects rely on substantive information more when evaluating women candidates. Our findings suggest that campaigns and campaign information may matter more for women candidates.

Background: Blepharospasm is treated with botulinum toxin, but obtaining satisfactory results is sometimes challenging. Objective: The aim is to conduct an exploratory trial of oral dipraglurant for blepharospasm. Methods: This study was an exploratory, phase 2a, randomized, double-blind, placebo-controlled trial of 15 participants who were assigned to receive a placebo or dipraglurant (50 or 100 mg) and assessed over 2 days, 1 and 2 hours following dosing. Outcome measures included multiple scales rated by clinicians or participants, digital video, and a wearable sensor. Results: Dipraglurant was well tolerated, with no obvious impact on any of the measurement outcomes. Power analyses suggested fewer subjects would be required for studies using a within-subject versus independent group design, especially for certain measures. Some outcome measures appeared more suitable than others. Conclusion: Although dipraglurant appeared well tolerated, it did not produce a trend for clinical benefit. The results provide valuable information for planning further trials in blepharospasm. (c) 2024 International Parkinson and Movement Disorder Society.

Given that political interest is one of the best predictors of political participation, it remains curious that the causes of interest are undertheorized and understudied. Notably absent from much of the research on political interest is an exploration of how variations in the nature of politics itself might have an impact on individual-level political interest. We develop a theory and a set of testable predictions about how partisanship interacts with the presence of a presidential (vs. midterm) election, the party of the sitting president, and elite polarization, to affect political interest. We report multilevel models that use ANES measures of political interest and partisanship and the DW-NOMINATE Senate polarization measure (from 1960 to 2008) and discuss the implications of our findings for the long-term prospects of an interested electorate.

Group consciousness is a pivotal concept used to understand the politics of many racial and ethnic groups. Originating from the study of African American politics, it has evolved into a unifying framework for analyzing the politics of most other racial and ethnic groups in the United States. Examining the construction and political relevance of group consciousness among identity groups is crucial for gaining a comprehensive perspective on race and ethnicity in politics. In this study, we employ an original survey involving 700 American Indians to empirically explore the multifaceted nature of group consciousness in this group. We investigate the factors associated with the development of group consciousness and how it intersects with their political attitudes and behaviors. Group consciousness emerges as a singular dimension that exhibits a strong correlation with political engagement and public opinion for American Indians. Our findings offer valuable insights into the distinctive nature of group consciousness within the American Indian population due to the uniqueness of their tribal political relationship. We also enhance the comprehension of how group consciousness operates in American politics by broadening the range of politicized identities employed for empirical exploration, shedding light on its impact on shaping political behavior.

To compare the inter-rater reliability (IRR) of five clinical rating scales for video-based assessment of hemifacial spasm (HFS) motor severity. We evaluated the video recordings of 45 HFS participants recruited through the Dystonia Coalition. In Round 1, six clinicians with expertise in HFS assessed the participants' motor severity with five scales used to measure motor severity of HFS: the Jankovic rating scale (JRS), Hemifacial Spasm Grading Scale (HSGS), Samsung Medical Center (SMC) grading system for severity of HFS spasms (Lee's scale), clinical grading of spasm intensity (Chen's scale), and a modified version of the Abnormal Involuntary Movement Scale (Tunc's scale). In Round 2, clinicians rated the same cohort with simplified scale wording after consensus training. For each round, we evaluated the IRR using the intraclass correlation coefficient [ICC (2,1) single-rater, absolute-agreement, 2-way random model]. The scales exhibited IRR that ranged from "poor" to "moderate"; the mean ICCs were 0.41, 0.43, 0.47, 0.43, and 0.65 for the JRS, HSGS, Lee's, Chen's, and Tunc's scales, respectively, for Round 1. In Round 2, the corresponding IRRs increased to 0.63, 0.60, 0.59, 0.53, and 0.71. In both rounds, Tunc's scale exhibited the highest IRR. For clinical assessments of HFS motor severity based on video observations, we recommend using Tunc's scale because of its comparative reliability and because clinicians interpret the scale easily without modifications or the need for consensus training.

How political actors choose which politics to focus on helps shape the outcome of the policy process. While the policy agenda of the federal government has received widespread attention, there is much less known about the policy agendas of the U.S. states. In this paper, we describe how and why states choose to have similar agendas. We rely on the Twitter activity of every state legislator in America to measure the attention that states pay to the categories developed in the Policy Agenda Project (PAP). We develop machine learning tools to measure the proportion of tweets from every state legislature from 2017 in each of the PAP policy topics. Our results show that states that the public-facing policy agenda of a state legislature is correlated with the level of legislative professionalism and the partisan and ideological politics of the state. These results further our understanding of state policymaking and agenda setting.

Measurement in the social sciences involves assigning values to particular empirical cases and plays a vital role in the research process, but it can be tricky to teach. Unless an undergraduate social sciences research methods course includes the collection of original data, many of the issues of measurement can seem abstract and arcane to students. To help illustrate how a social science researcher goes from a conceptualization to assigning values to cases, I developed a lecture that centers on the question "which artists are one-hit wonders?" I used the rules developed by Chris Molanphy to help students see how we can develop applicable methods for any possible case and make a measure that is both reliable and valid. The example also helps illustrate the difference between categorical and numerical variables by comparing the categorization of artists as one-hit wonders and the relative numerical value of the chart position of the artist's most successful song.

Introduction: A common view is that head tremor (HT) in cervical dystonia (CD) decreases when the head assumes an unopposed dystonic posture and increases when the head is held at midline. However, this has not been examined with objective measures in a large, multicenter cohort. Methods: For 80 participants with CD and HT, we analyzed videos from examination segments in which participants were instructed to 1) let their head drift to its most comfortable position (null point) and then 2) hold their head straight at midline. We used our previously developed Computational Motor Objective Rater (CMOR) to quantify changes in severity, amplitude, and frequency between the two postures. Results: Although up to 9% of participants had exacerbated HT in midline, across the whole cohort, paired t-tests reveal no significant changes in overall severity ( t = −0.23, p = 0.81), amplitude ( t = −0.80, p = 0.43), and frequency ( t = 1.48, p = 0.14) between the two postures. Conclusion: When instructed to first let their head drift to its null point and then to hold their head straight at midline, most patient’s changes in HT were below the thresholds one would expect from the sensitivity of clinical rating scales. Counter to common clinical impression, CMOR objectively showed that HT does not consistently increase at midline posture in comparison to the null posture.

Background Head tremor (HT) is a common feature of cervical dystonia (CD), usually quantified by subjective observation. Technological developments offer alternatives for measuring HT severity that are objective and amenable to automation. Objectives Our objectives were to develop CMOR (Computational Motor Objective Rater; a computer vision-based software system) to quantify oscillatory and directional aspects of HT from video recordings during a clinical examination and to test its convergent validity with clinical rating scales. Methods For 93 participants with isolated CD and HT enrolled by the Dystonia Coalition, we analyzed video recordings from an examination segment in which participants were instructed to let their head drift to its most comfortable dystonic position. We evaluated peak power, frequency, and directional dominance, and used Spearman's correlation to measure the agreement between CMOR and clinical ratings. Results Power averaged 0.90 (SD 1.80) deg2/Hz, and peak frequency 1.95 (SD 0.94) Hz. The dominant HT axis was pitch (antero/retrocollis) for 50%, roll (laterocollis) for 6%, and yaw (torticollis) for 44% of participants. One-sided t-tests showed substantial contributions from the secondary (t = 18.17, p < 0.0001) and tertiary (t = 12.89, p < 0.0001) HT axes. CMOR's HT severity measure positively correlated with the HT item on the Toronto Western Spasmodic Torticollis Rating Scale-2 (Spearman's rho = 0.54, p < 0.001). Conclusions We demonstrate a new objective method to measure HT severity that requires only conventional video recordings, quantifies the complexities of HT in CD, and exhibits convergent validity with clinical severity ratings.

Recent advances in deep neural networks have achieved outstanding success in natural language processing tasks. Interpretation methods that provide insight into the decision-making process of these models have received an influx of research attention because of the success and the black-box nature of the deep text classification models. Evaluation of these methods has been based on changes in classification accuracy or prediction confidence when removing important words identified by these methods. There are no measurements of the actual difference between the predicted important words and humans’ interpretation of ground truth because of the lack of interpretation ground truth. A large publicly available interpretation ground truth has the potential to advance the development of interpretation methods. Manual labeling important words for each document to create a large interpretation ground truth is very time-consuming. This paper presents (1) IDC, a new benchmark for quantitative evaluation of interpretation methods for deep text classification models, and (2) evaluation of six interpretation methods using the benchmark. The IDC benchmark consists of: (1) Three methods that generate three pseudo-interpretation ground truth datasets. (2) Three performance metrics: interpretation recall, interpretation precision, and Cohen’s kappa inter-agreement. Findings: IDC-generated interpretation ground truth agrees with human annotators on sampled movie reviews. IDC identifies Layer-wise Relevance Propagation and the gradient-by-input methods as the winning interpretation methods in this study.

Young adults are less likely to vote than older Americans, but they do not enter adulthood as blank slates. The political experiences before young adults are eligible to vote can shape their future likelihood of participation. In this paper, we explore how one particular event, the result of the 2016 presidential election, changed the likelihood of participation among young adults. We designed an original experiment that randomly assigned adults eligible to vote in a presidential election for the first time to be primed to remember their emotional reactions to the 2016 election. We found that participants who were asked to think about their emotional reaction to the 2016 United States presidential election were significantly more likely to say that they would vote in an election if one were held today. These findings suggest that, at least in the case of the 2016 election, reminding young adults of past political experience is likely to increase their motivation to vote.

PURPOSE:This study examined the relationship between voice quality and glottal geometry dynamics in patients with adductor spasmodic dysphonia (ADSD). METHOD:An objective computer vision and machine learning system was developed to extract glottal geometry dynamics from nasolaryngoscopic video recordings for 78 patients with ADSD. General regression models were used to examine the relationship between overall voice quality and 15 variables that capture glottal geometry dynamics derived from the computer vision system. Two experts in ADSD independently rated voice quality for two separate voice tasks for every patient, yielding four different voice quality rating models. RESULTS:All four of the regression models exhibited positive correlations with clinical assessments of voice quality (R 2s = .30-.34, Spearman rho = .55-.61, all with p < .001). Seven to 10 variables were included in each model. There was high overlap in the variables included between the four models, and the sign of the correlation with voice quality was consistent for each variable across all four regression models. CONCLUSION:We found specific glottal geometry dynamics that correspond to voice quality in ADSD.

Abstract Objective Deviated head posture is a defining characteristic of cervical dystonia (CD). Head posture severity is typically quantified with clinical rating scales such as the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS). Because clinical rating scales are inherently subjective, they are susceptible to variability that reduces their sensitivity as outcome measures. The variability could be circumvented with methods to measure CD head posture objectively. However, previously used objective methods require specialized equipment and have been limited to studies with a small number of cases. The objective of this study was to evaluate a novel software system—the Computational Motor Objective Rater (CMOR)—to quantify multi‐axis directionality and severity of head posture in CD using only conventional video camera recordings. Methods CMOR is based on computer vision and machine learning technology that captures 3D head angle from video. We used CMOR to quantify the axial patterns and severity of predominant head posture in a retrospective, cross‐sectional study of 185 patients with isolated CD recruited from 10 sites in the Dystonia Coalition. Results The predominant head posture involved more than one axis in 80.5% of patients and all three axes in 44.4%. CMOR's metrics for head posture severity correlated with severity ratings from movement disorders neurologists using both the TWSTRS‐2 and an adapted version of the Global Dystonia Rating Scale (rho = 0.59–0.68, all p <0.001). Conclusions CMOR's convergent validity with clinical rating scales and reliance upon only conventional video recordings supports its future potential for large scale multisite clinical trials.

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White evangelical Protestants are the most skeptical major religious group in the United States regarding climate change. While their position of political influence in the Republican coalition is widely recognised, the full range of effects of this position on evangelicals' climate opinions is not. To move research on evangelicals from the margins of climate change opinion research, we review and integrate the interdisciplinary literature on US evangelicals, climate change, and politics. In assessing this literature, we identify three areas in need of further research. First, there is a critical need for more research on the climate attitudes of evangelicals of color, who comprise a growing share of the evangelical tradition in the US. Second, highlighting the Christian Right's active engagement in the climate debate, we identify a need for more experimental work examining how cues from religious elites may shape evangelicals' opinions. Finally, we suggest that to better harness insights across disciplines, researchers must become more explicitly aware of how different disciplines conceptualize temporality. Attending to temporal scale suggests that a new approach is needed to test how dominion beliefs, which are widely thought to be an important theological driver of climate skepticism, operate. We also suggest that two factors that appear to play a weak or limited role in driving climate skepticism over the short term (anti-science attitudes and evangelical religiosity) may in fact play a significant role in driving skepticism over the medium term. This article is categorized under: Perceptions, Behavior, and Communication of Climate Change > Perceptions of Climate Change Trans-Disciplinary Perspectives > Humanities and the Creative Arts

Background: A defining characteristic of dystonia is its position-dependence. In cervical dystonia (CD), sensory tricks ameliorate head tremor (HT). But it remains unknown whether raising the arms alone has the same impact. Methods: We analyzed data collected from patients enrolled by the Dystonia Coalition. For 120 patients with HT, we assessed how raising their arms without touching their head changed their HT severity. Results: Forty-eight out of 120 patients exhibited changes in HT severity when raising their arms. These patients were more likely to exhibit decreases in HT severity (N = 35) than increases (N = 13, χ2 (1, N = 48) = 10.1, p = 0.002). Demographic factors and sensory trick efficacy were not significant predictors of whether HT severity changed when raising their arms. Discussion: Raising the arms without touching the head is a posture that can reduce HT severity in some CD patients. Our results extend the concept of position-dependent motor symptoms in CD to include the position of the arms. Highlights Head tremor (HT) is a prevalent symptom of cervical dystonia (CD) that can often be disabling. This study demonstrates that raising the arms without touching the head is a posture that can reduce HT severity in some CD patients. Our findings also identify a novel form of position-dependence in CD.