Intraclass correlation coefficient (ICC) estimates are necessary for several statistical techniques. Researchers need accurate ICC estimates when conducting prospective power analyses for clustered data scenarios. In addition, meta-analysts require reasonable ICC values when adjusting effect size estimates to account for clustered primary study data or to correct for psychometric artifacts when using the ICC as a reliability measure. The validity of these analyses hinges on the accuracy of the ICC estimate. Beyond these secondary analyses, ICC estimates have been used as the focal outcome of meta-analysis itself to obtain a pooled measure of agreement, reliability, or the influence of a cluster’s effect. This study evaluates how well meta-analytically pooled ICC estimates recover the population ICC parameter value when using different ICC variance formulas as the inverse variance weights used in the pooling. We found that the variance formula that uses a normalizing transformation performs best across most conditions.

Punching shear failure in slab-column connections is a brittle collapse mode that threatens the safety of flat reinforced concrete (RC) slabs. Conventional design provisions are generally conservative but exhibit inconsistencies across geometric and material variations. This study develops an eXtreme Gradient Boosting (XGBoost) model to predict the ultimate punching shear capacity of flat RC slabs, using a database of experimental results categorized by four different geometric domains, including square slab with square column, circular slab with circular column, square slab with circular column, and circular slab with square column, covering the geometric, materials strength, and reinforcement properties of input parameters. The model achieved high predictive accuracy across the domains with coefficient of determination (R2) values > 0.930 in unseen testing datasets with minimal bias (0.994–1.006) and reduced scatter. Model interpretability, addressed through the SHapley Additive exPlanations analysis, confirmed slab thickness and average effective depth as the most critical predictors of shear capacity, followed by concrete strength and reinforcement parameters, while boundary condition parameters showed negligible influence due to the predominance of interior column cases. These findings demonstrate that XGBoost provides accurate, reliable, and interpretable predictions of punching shear capacity, offering a data-driven alternative to code-based methods and supporting safer and more consistent design of flat RC slabs.

Following a trend across the sciences, recent studies in lithic analysis have embraced the ideal of replicability. Recent large-scale studies have demonstrated that high replicability is achievable under controlled conditions and have proposed strategies to improve it in lithic data recording. Although this focus has yielded important methodological advances, we argue that an overemphasis on replicability risks narrowing the scope of archaeological inquiry. More specifically, we show (1) that replicability alone does not guarantee reliability, interpretive value, or cost effectiveness, and (2) that archaeological data often involve unavoidable ambiguity due to preservation, analyst background, and the nature of lithic variability itself. Instead of allowing replicability to dictate research priorities, we advocate for a problem-driven, pluralistic approach that tailors methods to research questions and balances replicable measures with interpretive depth. This has practical implications for training, publishing, and funding policy. We conclude that Paleolithic archaeology must engage with the replicability movement on its own terms—preserving methodological diversity while maintaining scientific credibility.

Bilinguals vary in their daily-life language use and switching behaviours, which are also frequently studied in relation to other processes (e.g., executive control). Measuring daily-life language use and switching often relies on self-reported questionnaires, but little is known about the validity of these questionnaires. Here, we present two studies examining test–retest reliability and validity of language-use questionnaires (relative to Ecological Momentary Assessment, Study 1) and language-switching questionnaires and tasks (relative to recorded daily-life conversations, small-scale Study 2). Test–retest reliability and validity of the LSBQ (Anderson et al., 2018) were high and moderate, respectively, suggesting this questionnaire can capture daily-life language use well. Although only examined with a small sample size, Study 2 suggested relatively low validity of most language-switching questionnaires, with short language-production tasks potentially offering a more valid assessment. Together, these studies suggest that tools are available to reliably capture language use and switching with (a certain degree of) validity.

Mental health conditions among youths are increasing rapidly, taking into consideration their biological, psychological and social development in the time of technological advancement with its associated challenges. Therefore, this study examined the psychometric properties of eight mental health scales among Ghanaian youth. A total of 708 youths (62.1% females; 10–29 years) from junior high schools, senior high schools and a university were recruited to respond to measures on depression, anxiety, somatic symptoms, obsessive–compulsive symptoms, insomnia, smartphone application-based addiction, internet addiction, life satisfaction, stress and cognitive fatigue. Confirmatory factor analysis (CFA) and Pearson’s r were used to analyse the data. The findings indicated acceptable CFA fit for all scales (comparative fit index [CFI] >0.9, Tucker–Lewis index [TLI] >0.9, root mean square error of approximation [RMSEA] <0.08 and standardized root mean square residual [SRMR] <0.08), and internal reliability was satisfactory (Cronbach’s α = 0.774–0.868 and McDonald’s ω = 0.775–0.870). Correlation analyses showed significant relationships between all the measures except for life satisfaction and internet addiction, and stress and life satisfaction. Both the CFA indices and correlation analyses indicate that all the mental health measures demonstrate acceptable initial evidence of reliability and construct validity.

We revisit the question of how to include parameter uncertainty in univariate parametric models of losses and loss ratios. We first review the statistical theory for including parameter uncertainty based on right Haar priors (RHPs), which applies to many commonly used models. In this theory, the prior is chosen in such a way as to ensure matching between predicted probabilities and the relative frequencies of future outcomes in repeated tests. This property is known as reliability, or calibration. We then test priors for including parameter uncertainty in a number of models not covered by RHP theory. For these models, we find priors that generate predictions that are more reliable than predictions based on maximum likelihood, although they are not perfectly reliable. We discuss numerical schemes that can be used to generate Bayesian predictions, including a novel use of asymptotic expansions, and we include an example in which we show the impact of including parameter uncertainty in the modeling of extreme hurricane losses. The tail loss estimates show material increases due to the inclusion of parameter uncertainty. Finally, we describe a new software library that makes it straightforward to apply the methods we describe.

Democracy measurement is an ever growing and increasingly important research area. Nevertheless, lively discussions concerning the qualities of different measurement approaches are seldom combined with an adequate perspective on the underlying methodological framework. This article argues that a substantial theoretical perspective is only a sufficient condition for improving contemporary democracy measurement. Theoretical considerations have to be accompanied by an equally well-developed measurement concept. On the basis of examples taken from prominent approaches, potential for improvement becomes obvious. Any improvement is not just an end in itself but necessary if these measures are used as variables in all areas of research.

The reliability of volunteers is a major concern for many nonprofit organizations. To address this problem in more detail, we develop a theoretical model of volunteer reliability based on psychological contract theory. By taking this perspective as a starting point, we explore how individual volunteer characteristics, organizational factors, and sociological developments shape the exchange of inducements and contributions between volunteers and nonprofit organizations. We discuss how these factors can create tensions in the psychological contract and determine the extent to which volunteers behave reliably. As such, we develop a theoretical framework for addressing the reliability problem in volunteer management.

Over recent decades, comparative political scientists have developed new measures at a rate of knots that evaluate the quality of democratic regimes. These indices have been broadly applied to assess the quality of democracy cross-nationally and to test the generalisability of theories regarding its causes and effects. However, the validity of these inferences is jeopardised by the fact that the quality of democracy is an abstract and contested concept. In order to address this eventuality, researchers constructing indices measuring the quality of democracy as well as researchers applying these indices should critically examine the quality of the indices. Owing to the absence of a standardised framework that is both suitable for the evaluation of contested concepts and that includes explicit coding rules so as to be directly applicable, this article seeks to fill this gap. The application of our framework is demonstrated by an evaluation of the Sustainable Governance Indicators, the Global Democracy Ranking and the Democracy Barometer. As indicated by our evaluation, the framework is a practical tool that helps to assess the conceptual foundation, validity, reliability and replicability of indices. In addition, it can be used to study the quality of indices in a comparable manner.

While there is an abundant use of macro data in the social sciences, little attention is given to the sources or the construction of these data. Owing to the restricted amount of indices or items, researchers most often apply the ‘available data at hand’. Since the opportunities to analyse data are constantly increasing and the availability of macro indicators is improving as well, one may be enticed to incorporate even qualitatively inferior indicators for the sake of statistically significant results. The pitfalls of applying biased indicators or using instruments with unknown methodological characteristics are biased estimates, false statistical inferences and, as one potential consequence, the derivation of misleading policy recommendations. This Special Issue assembles contributions that attempt to stimulate the missing debate about the criteria of assessing aggregate data and their measurement properties for comparative analyses.

Disasters significantly challenge societal resilience, individual psychological health, and sustainable development. This study aimed to culturally adapt the Disaster Adaptation and Resilience Scale (DARS) into Turkish and evaluate its psychometric properties for use in Türkiye. Participants (N = 335) aged 18 and older who had experienced a disaster in the past 5 years completed the Turkish version of the DARS following rigorous translation and expert review procedures. Exploratory and confirmatory factor analyses revealed a 5-factor structure: Problem-Solving, Optimism, Stress Management, Social Resources, and Physical Resources, accounting for 61.3% of the total variance. Internal consistency was high (Cronbach’s Alpha = 0.910), with subscale values ranging from 0.785 to 0.901. Test-retest reliability and discriminant validity were also established. The Turkish DARS is a valid and reliable tool for evaluating disaster-related adaptation and resilience. Its implementation supports sustainable mental health responses and community preparedness in disaster-prone regions.