Thomas Schelling argued that “The most spectacular event of the past half century is one that did not occur. We have enjoyed sixty years without nuclear weapons exploded in anger.” To this, he added a question: “Can we make it through another half dozen decades?” Contemporary technological innovation, weapons proliferation, increased modernization efforts, and nuclear saber-rattling have made Schelling's question an urgent one. Recently, there has been an explosion in scholarship attempting to test the resilience of nonuse. These scholars have focused primarily on methodological innovations, generating an impressive body of evidence about the future of nonuse. Yet we argue that this literature is theoretically problematic: it reduces mechanisms of nuclear nonuse to a “rationalist” versus “normative” dichotomy which obscures the distinct pathways to nuclear (non)use within each theoretical framework. With rationalist theories, the current literature commits the sin of conflation, treating what should be distinct mechanisms—cost and credibility—as a single causal story. With normative theories, scholars have committed a sin of omission, treating norms as structural and overlooking mechanisms of norm contestation. We show that teasing out these different causal pathways reveals radically different expectations about the future of nonuse, especially in a world of precision nuclear weapons.

Wittgenstein’s Private Language Argument is one of the most famous arguments in philosophy. It is a surprisingly tricky argument to understand. Some philosophers think it’s a good argument. Others disagree. In fact they even disagree about what the argument actually is. This short essay gives three different interpretations of the argument and explains why I believe none succeed.

A mixed-effects location scale model allows researchers to study within- and between-person variation in repeated measures. Key components of the model include separate variance models to study predictors of the within-person variance, as well as predictors of the between-person variance of a random effect, such as a random intercept. In this paper, a latent variable mixed-effects location scale model is developed that combines a longitudinal common factor model and a mixed-effects location scale model to characterize within- and between-person variation in a common factor. The model is illustrated using daily reports of positive affect and daily stressors for a large sample of adult women.

Emanating beyond the confines of academia, the poignant narrative of the renowned Turkish thespian Afife Jale has garnered widespread recognition within Türkiye. Amid a pantheon of successors, her tale stands as the most profoundly heartrending. It has been immortalized through theatrical productions and cinematic adaptations. Despite the widespread familiarity with her story, the enigmatic underpinnings of her tragedy have perpetually shrouded it in mystery. In an effort to cast light upon the chronicle of her life, a convergence of political and societal truths has emerged. Afife Jale's story, in its very essence, embodies the ideals expounded by Joan W. Scott. The realm of feminist historiography endeavors to bring prominence to women's narratives, elucidating their endeavors to champion their entitlements and autonomy within historical contexts. It seeks to delve into the causalities behind the historical obscurity that has veiled women's contributions, while also revealing the obstructions that have curtailed their authority and efficacy. This article aspires to achieve this objective by scrutinizing the careers of the first Turkish Muslim actresses, Afife Jale (1902–41) and Bedia Muvahhit (1896–1994), who commenced their artistic journeys at the onset of the twentieth century. Whereas Afife Jale's stage debut in 1920 coincided with the twilight of Ottoman rule, Bedia Muvahhit made her inaugural appearance in 1923, the very year that saw the founding of the Turkish Republic. Despite this seemingly minor difference, the professional journeys of these two actresses were characterized by stark disparities. Afife Jale bore the weight of authoritarian oppression and persecution, and her legacy remained largely overlooked, even after the Turkish Republic was founded. In contrast, Bedia Muvahhit thrived under the patronage and backing of the political elite, leading to a lengthy and prosperous career.

Several decades ago, the National Park Service's Chaco Project revealed evidence for widespread ornament manufacture at small sites (small houses) in Chaco Canyon, New Mexico, as well as possible workshop-scale production at two of these locations. Given that consumption of finished jewelry items is clearly concentrated at large sites (great houses), it was suggested that lapidary production was part of a larger corporate political strategy, in which goods produced in surrounding small houses were used to sustain communal events related to construction activities and ritual performances at great houses. This article addresses a critical gap in this narrative—ornament production at great houses. Using Pueblo Bonito as a case study, I present the results of a systematic analysis of lapidary tools from the site and characterize the nature of on-site ornament manufacture. I find evidence that significant jewelry-making was occurring at Pueblo Bonito, at least on par with previously documented small-house jewelry workshops, and that a portion of this was embedded within elite households. These results require us to reconsider the role of ornament production in Chacoan political economy.

The study of late antique and early medieval urban religion in the Iberian Peninsula suffers from a dearth of datable and localizable source material. Martyr passions abound, as do liturgical texts, but these almost always survive only in later manuscripts, filtered through monastic libraries and scriptoria. How far these copies preserve the genuine texts performed in earlier cult remains an open question. This article intervenes in this discussion by focusing on a somewhat unusual cult known as the ‘Innumerable’ or ‘Eighteen’ martyrs of Zaragoza. The cult’s Passion text survives in two variant redactions. One originates from the sixth-century city of Zaragoza, the cult’s center, while the other derives from the Carolingian monastery of Saint-Germain-des-Prés in ninth-century Paris. These divergent lines of transmission make possible a comparative study that both elucidates the process of ‘monasticization’ that the Passion underwent in Carolingian hands and vindicates the relative conservatism of the Iberian lines of transmission. Indeed, the Iberian manuscripts retain a remarkable amount of distinctly local material, thereby presenting a rich case study in the civic and oral sensibilities of martyr passions. This article places the Passion back in its civic context, amidst the complex and fractious religious life of Visigothic Zaragoza, complementing the burgeoning interest in communal liturgical and ceremonial life evident among historical liturgists and musicologists. More broadly, it shows that Iberian passions are indispensable texts for historians of urban religious expression and civic Christianity in the Visigothic period.

Latent variable models have been playing a central role in psychometrics and related fields. In many modern applications, the inference based on latent variable models involves one or several of the following features: (1) the presence of many latent variables, (2) the observed and latent variables being continuous, discrete, or a combination of both, (3) constraints on parameters, and (4) penalties on parameters to impose model parsimony. The estimation often involves maximizing an objective function based on a marginal likelihood/pseudo-likelihood, possibly with constraints and/or penalties on parameters. Solving this optimization problem is highly non-trivial, due to the complexities brought by the features mentioned above. Although several efficient algorithms have been proposed, there lacks a unified computational framework that takes all these features into account. In this paper, we fill the gap. Specifically, we provide a unified formulation for the optimization problem and then propose a quasi-Newton stochastic proximal algorithm. Theoretical properties of the proposed algorithms are established. The computational efficiency and robustness are shown by simulation studies under various settings for latent variable model estimation.

The CANDECOMP/PARAFAC (CP) model decomposes a three-way array into a prespecified number of R factors and a residual array by minimizing the sum of squares of the latter. It is well known that an optimal solution for CP need not exist. We show that if an optimal CP solution does not exist, then any sequence of CP factors monotonically decreasing the CP criterion value to its infimum will exhibit the features of a so-called “degeneracy”. That is, the parameter matrices become nearly rank deficient and the Euclidean norm of some factors tends to infinity. We also show that the CP criterion function does attain its infimum if one of the parameter matrices is constrained to be column-wise orthonormal.

This article explores the significance of the Kenya National Human Rights Commission (‘KNCHR’) and the National Gender and Equality Commission (‘NGEC’), as independent ‘fourth branch’ institutions protecting democracy (‘IPDs’) in Kenya, in promoting and protecting human rights, democracy and addressing poverty and economic inequality. It provides a conceptual background for the establishment of the two Commissions and evaluates their functions and effectiveness compared to civil society organisations with similar roles. It then examines the unique role of the Commissions in addressing poverty and economic inequality and their accomplishments in upholding the rule of law, democratic ideals and human rights in Kenya. The article also analyses the challenges faced by the Commissions in achieving their goals and the opportunities arising from their emergence as fourth branch IPDs. Finally, it concludes that the constitutional entrenchment of the KNCHR and NGEC provides them with credibility, legitimacy and freedom to carry out their work effectively. However, resource constraints and dependence on political goodwill may hinder their effectiveness in translating human rights, particularly socio-economic rights, into reality. Despite these challenges, the Commissions’ oversight, investigation and complaint handling roles are critical in preventing and addressing poverty and economic inequality through data-driven transformation and collaborative efforts.

The emergence of computer-based assessments has made response times, in addition to response accuracies, available as a source of information about test takers’ latent abilities. The development of substantively meaningful accounts of the cognitive process underlying item responses is critical to establishing the validity of psychometric tests. However, existing substantive theories such as the diffusion model have been slow to gain traction due to their unwieldy functional form and regular violations of model assumptions in psychometric contexts. In the present work, we develop an attention-based diffusion model based on process assumptions that are appropriate for psychometric applications. This model is straightforward to analyse using Gibbs sampling and can be readily extended. We demonstrate our model’s good computational and statistical properties in a comparison with two well-established psychometric models.

Generalized structured component analysis (GSCA) is a multivariate method for examining theory-driven relationships between variables including components. GSCA can provide the deterministic component score for each individual once model parameters are estimated. As the traditional GSCA always standardizes all indicators and components, however, it could not utilize information on the indicators’ scale in parameter estimation. Consequently, its component scores could just show the relative standing of each individual for a component, rather than the individual’s absolute standing in terms of the original indicators’ measurement scales. In the paper, we propose a new version of GSCA, named convex GSCA, which can produce a new type of unstandardized components, termed convex components, which can be intuitively interpreted in terms of the original indicators’ scales. We investigate the empirical performance of the proposed method through the analyses of simulated and real data.

We study the robustness of Krupka and Weber's method (2013) for eliciting social norms. In two online experiments with more than 1200 participants on Amazon Mechanical Turk, we find that participants’ response patterns are invariant to differences in the salience of the monetarily incentivized coordination aspect. We further demonstrate that asking participants for their personal first- and second-order beliefs without monetary incentives results in qualitatively identical responses in the case that beliefs and social norms are well aligned. Overall, Krupka and Weber's method produces remarkably robust response patterns.

Whenever statistical analyses are applied to multiply imputed datasets, specific formulas are needed to combine the results into one overall analysis, also called combination rules. In the context of regression analysis, combination rules for the unstandardized regression coefficients, the t-tests of the regression coefficients, and the F-tests for testing $R^2$\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$R^{2}$$\end{document} for significance have long been established. However, there is still no general agreement on how to combine the point estimators of $R^2$\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$R^{2}$$\end{document} in multiple regression applied to multiply imputed datasets. Additionally, no combination rules for standardized regression coefficients and their confidence intervals seem to have been developed at all. In the current article, two sets of combination rules for the standardized regression coefficients and their confidence intervals are proposed, and their statistical properties are discussed. Additionally, two improved point estimators of $R^2$\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$R^{2}$$\end{document} in multiply imputed data are proposed, which in their computation use the pooled standardized regression coefficients. Simulations show that the proposed pooled standardized coefficients produce only small bias and that their 95% confidence intervals produce coverage close to the theoretical 95%. Furthermore, the simulations show that the newly proposed pooled estimates for $R^2$\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$R^{2}$$\end{document} are less biased than two earlier proposed pooled estimates.

Studies with sensitive questions should include a sufficient number of respondents to adequately address the research interest. While studies with an inadequate number of respondents may not yield significant conclusions, studies with an excess of respondents become wasteful of investigators’ budget. Therefore, it is an important step in survey sampling to determine the required number of participants. In this article, we derive sample size formulas based on confidence interval estimation of prevalence for four randomized response models, namely, the Warner’s randomized response model, unrelated question model, item count technique model and cheater detection model. Specifically, our sample size formulas control, with a given assurance probability, the width of a confidence interval within the planned range. Simulation results demonstrate that all formulas are accurate in terms of empirical coverage probabilities and empirical assurance probabilities. All formulas are illustrated using a real-life application about the use of unethical tactics in negotiation.

Many studies in fields such as psychology and educational sciences obtain information about attributes of subjects through observational studies, in which raters score subjects using multiple-item rating scales. Error variance due to measurement effects, such as items and raters, attenuate the regression coefficients and lower the power of (hierarchical) linear models. A modeling procedure is discussed to reduce the attenuation. The procedure consists of (1) an item response theory (IRT) model to map the discrete item responses to a continuous latent scale and (2) a generalizability theory (GT) model to separate the variance in the latent measurement into variance components of interest and nuisance variance components. It will be shown how measurements obtained from this mixture of IRT and GT models can be embedded in (hierarchical) linear models, both as predictor or criterion variables, such that error variance due to nuisance effects are partialled out. Using examples from the field of educational measurement, it is shown how general-purpose software can be used to implement the modeling procedure.

The assumption of latent monotonicity is made by all common parametric and nonparametric polytomous item response theory models and is crucial for establishing an ordinal level of measurement of the item score. Three forms of latent monotonicity can be distinguished: monotonicity of the cumulative probabilities, of the continuation ratios, and of the adjacent-category ratios. Observable consequences of these different forms of latent monotonicity are derived, and Bayes factor methods for testing these consequences are proposed. These methods allow for the quantification of the evidence both in favor and against the tested property. Both item-level and category-level Bayes factors are considered, and their performance is evaluated using a simulation study. The methods are applied to an empirical example consisting of a 10-item Likert scale to investigate whether a polytomous item scoring rule results in item scores that are of ordinal level measurement.

Several anthropological and historical studies based on comparative research show that there is no universal concept of ‘cleanliness’ or ‘hygiene’ common to all cultures in all historical periods. Ideas about what is considered clean, the means used to keep persons, objects and places clean, and the frequency or appropriate timing of cleaning actions differ between cultures, and even within a given culture. The latter implies that, sometimes, these differences depend on social position, mainly because this position allows or prevents certain cleansing practices. In addition, the concept of ‘cleanliness’ may sometimes be intertwined with the idea of ‘purity’, and thus be related to religious beliefs and practices. The present article examines the concept of ‘hygiene’ for the case of the Hittites, and aims to do so from an historical perspective by reflecting on modern vocabulary related to hygiene, investigating Hittite terminology related to cleanliness and analysing textual sources. Archaeological evidence will be examined alongside the textual sources to establish correlations regarding locations and objects used for hygienic practices. The objectives are to investigate who practiced cleanliness and when in Hittite culture, how and where these practices occurred, and what objects were used, as well as how the Hittites understood hygiene and whether perceptions and practices varied by social group.