The rise of China as a global power has been a prominent feature in international politics. Simultaneously, the United States has been engaged in ongoing conflicts in the Middle East and South Asia for the past two decades, requiring a significant commitment of resources, focus, and determination. This paper investigates how third-party countries react to the United States’ preoccupation with these conflicts, particularly in terms of diplomatic co-operation and alignment. We introduce a measure of US distraction and utilize network-based indicators to assess diplomatic co-operation or alignment. Our study tests the hypothesis that when the US is distracted, other states are more likely to co-operate with its principal rival, China. Our findings support this hypothesis, revealing that increased co-operation with China is more probable during periods of US distraction. However, a closer examination of state responses shows that democracies distance themselves from China under these circumstances, while non-democracies move closer.

Al-Hoorie et al. (2024) have described L2 Motivational Self System research as having a “validation crisis.” In this response, I offer a brief history of recent motivation research to contextualize how we reached this point. I then discuss measurement invariance testing, the purpose of which is to ensure that the proposed measurement model holds across groups or time. Crucially, invariance testing is a necessary precursor to subsequent analyses because if invariance is not upheld, it is impossible to know whether differences reflect true underlying differences in the latent construct or are simply the byproduct of a changing measurement model. I argue that by combining measurement invariance testing with open science practices, we can create and validate better measurement models while cultivating a better understanding of their scope of application.

Rapid advances in psychology and technology open opportunities and present challenges beyond familiar forms of educational assessment and measurement. Viewing assessment through the perspectives of complex adaptive sociocognitive systems and argumentation helps us extend the concepts and methods of educational measurement to new forms of assessment, such as those involving interaction in simulation environments and automated evaluation of performances. I summarize key ideas for doing so and point to the roles of measurement models and their relation to sociocognitive systems and assessment arguments. A game-based learning assessment SimCityEDU: Pollution Challenge! is used to illustrate ideas.

Identifying farmers’ attitudes to farm animal welfare (FAW) is an important step in determining farmers’ efforts to improve FAW, knowledge of which is of particular importance for understanding how the living conditions of production animals are determined. This study developed a hypothetical model of farmers’ attitudes to FAW, including the antecedents of these attitudes and possible influences on FAW-related behaviour. Two models for empirical measurement of attitudes, namely formative and reflective models, were also evaluated and compared. The results suggested that choice of measurement model considerably influences conceptualisation of attitudes and that there may be considerable model misspecifications in previous literature relating to farmers’ FAW attitudes. Existing literature on farmers’ FAW attitudes was reviewed with the aim of providing a preliminary indication of the coverage of farmers’ FAW attitudes. A need for future research related to farmers’ attitudes to FAW was identified.