We identify a novel pathway that links financial globalization to politics. We emphasize the effect of globalization on the relationship between governments and domestic business owners, who, like all borrowers, are subject to “Global Credit Cycles” originating from the U.S. Downturns in these cycles, stemming from high U.S. interest rates, reduce credit availability, depress asset prices, and broadly worsen the outlook for private sector profits. While politicians have limited power to address the underlying financial conditions, they can adopt business-friendly politics to signal their willingness to compensate firms for the higher borrowing costs driven by higher U.S. interest rates. We support our argument with evidence from party manifestos across 59 countries, covering 1963 to 2017. Our paper documents a new connection between global credit cycles and party positions during an era of largely unrestricted capital mobility.

Since stochastic differential equations (SDEs) driven by G-Brownian motion are of great importance in modeling situations that incorporate ambiguity, it is essential to address efficient numerical schemes to approximate the solution of such equations. The stream of research related to the numerical solutions of G-SDEs under standard assumptions is to some extent well understood. In this note, we are interested in designing an implicit $\theta$-Euler–Maruyama scheme to approximate the solution of G-SDEs under locally Lipschitz continuous coefficients. The convergence of the proposed scheme is established using the stopping time technique. In addition, we investigate the exponentially/quasi-surely asymptotic stability property of the scheme.

In times of crisis, such as pandemics or social injustice, people often talk about the importance of solidarity, standing together for a common cause. However, this term, while powerful, can sometimes leave people out, especially those who do not fit neatly into shared identities or experiences. Our paper examines how the concept of solidarity can unintentionally exclude individuals, obscure power disparities, or even be exploited by political or corporate interests. Rather than abandoning the concept, we suggest adding a new term: convergence. This word captures the idea of people coming together from different backgrounds to work towards shared goals, without needing to be the same or agree on everything. By combining solidarity with convergence, we can build more inclusive, transparent, and dynamic ways of working together in today’s complex world. This shift in language may help us navigate global challenges more fairly and collaboratively.

We propose a novel approach to numerically approximate McKean–Vlasov stochastic differential equations (MV-SDEs) using stochastic gradient descent (SGD) while avoiding the use of interacting particle systems (IPSs) and the associated simulation costs required to achieve the ‘propagation of chaos’ limit. The SGD technique is deployed to solve a Euclidean minimization problem, obtained by first representing the MV-SDE as a minimization problem over the set of continuous functions of time, and then approximating the domain with a finite-dimensional sub-space. Convergence is established by proving certain intermediate stability and moment estimates of the relevant stochastic processes, including the tangent processes. Numerical experiments illustrate the competitive performance of our SGD-based method compared with the IPS benchmarks. This work offers a theoretical foundation for using the SGD method in the context of numerical approximation of MV-SDEs, and provides analytical tools to study its stability and convergence.

In this paper, we are mainly devoted to the limiting behaviour of smooth inertial manifolds for a class of random retarded differential equations with a singular parameter $\delta$ and their Galerkin approximations, which have not been considered before. Under appropriate conditions, we show not only that the inertial manifolds for this class of random retarded equations converge pointwise to those of the corresponding stochastic equations driven by white noise as $\delta\rightarrow 0$, but also that the inertial manifolds of their Galerkin approximations converge pointwise to those of stochastic equations driven by white noise described above under the simultaneous limits $\delta\rightarrow 0$ and $M\rightarrow +\infty$, where $M$ denotes the dimension index of the orthogonal projection operator $P_M$ in the Galerkin scheme.

The English past tense contains pockets of variation, where regular and irregular forms compete (e.g. learned/learnt, weaved/wove). Individuals vary considerably in the degree to which they prefer irregular forms. This article examines the degree to which individuals may converge on their regularization patterns and preferences. We report on a novel experimental methodology, using a cooperative game involving nonce verbs. Analysis of participants' postgame responses indicates that their behavior shifted in response to an automated co-player's preferences, on two dimensions. First, players regularize more after playing with peers with high regularization rates, and less after playing with peers with low regularization rates. Second, players' overall patterns of regularization are also affected by the particular distribution of (ir)regular forms produced by the peer.

We model the effects of the exposure on participants' morphological preferences, using both a rule-based model and an instance-based analogical model (Nosofsky 1988, Albright & Hayes 2003). Both models contribute separately and significantly to explaining participants' pre-exposure regularization processes. However, only the instance-based model captures the shift in preferences that arises after exposure to the peer. We argue that the results suggest an account of morphological convergence in which new word forms are stored in memory, and on-line generalizations are formed over these instances.

Increasing societal heterogeneity, changing demographics, and increasing public debt and fiscal constraints have recently challenged traditional “regime” approaches to welfare state development. Some scholars argue, against this background, that welfare states might plausibly move out of their “regime container” by opting in favor of similar solutions and responses. This potential trend toward “convergence” might, furthermore, be facilitated by the widespread use of new public management ideas and techniques for “reinventing government” by adopting market solutions to public problems. This article investigates whether such trends of convergence can be identified by comparing three different countries each traditionally looked upon as belonging to different welfare state regimes: Denmark, Germany, and the United States. More specifically the article looks at one important segment of welfare state activity, namely social services and related health care. To further focus the analysis, special attention is devoted to the changing role played by the third sector in delivering services. The research design, thus, differs from most comparative welfare state research. Instead of analyzing a broad set of quantitative indicators in a large number of countries, it is scrutinized how some of the same problem pressures and policy ideas are being interpreted and implemented in a small number of countries within one policy area. The analysis reveals that trends of convergence—conceptualized along four dimensions: ideas, regulation, mix of providers, and revenue mix—can be identified across the three cases, though this does not mean that the market share of nonprofit providers becomes the same. The study also reveals that fundamental aspects of state–nonprofit relations persist despite trends of convergence.

This article examines the role of sociolinguistic expectations in linguistic convergence, using glide-weakened /aɪ/—a salient feature of Southern US English—as a test case. I present the results of two experiments utilizing a novel experimental paradigm for eliciting convergence—the WORD-NAMING GAME task—in which participants read aloud (baseline) or hear (exposure) clues describing particular words and then give their guesses out loud. Participants converged toward a Southern-shifted model talker by producing more glide-weakened tokens of /aɪ/, without ever hearing the model talker produce this vowel. Participants in the control (Midland talker) condition exhibited no such response. Convergence was facilitated by both living in the South and producing less-weakened baseline /aɪ/ glides, but attitudinal and domain-general individual-differences measures did not reliably predict convergence behaviors. Results are discussed in terms of implications for the cognitive mechanisms underlying convergence behaviors and the mental representations of sociolinguistic knowledge.

This article focuses on the role of congruence in Creole formation and development, using a competition-and-selection framework. The proposal is that the similarities (the congruent features) that speakers perceive between the languages in contact are favored to participate in the emergence and development of a new language. Specifically, I illustrate how morphosyntactic and semantic features are more likely to be selected into the grammatical makeup of a given Creole when they PREEXIST and are shared by some of the source languages present in its linguistic ecology. This is empirically supported in this article by numerous case studies and a survey of congruent features in twenty contact languages across nineteen grammatical and lexical domains. In order to show how congruence operates, I propose a model of matter and pattern mapping, adapted to the multilingual setting in which Creole languages emerge.

This study investigated the question of how civil society groups cross political, cultural, social, economic, and language boundaries to find common ground and to act collectively in coalitions to effect international change. A set of constituents emerged in answer to the research question; Complementarity, Speed and Democracy, Rules of Engagement, Contingent Alliance, and Convergence. Convergence emerged as a central and unifying construct. Convergence is the uniting of people who are different, or even opposed, around a common cause. It is based on the presumption that diversity is critical to coalition success and that it needs be employed to leverage its many potential benefits. The analyses led to the conceptualization of the Convergence System, a model that employs global civil society (GCS) diversity to discern complementarity within GCS coalitions, to discover Points of Convergence, and to facilitate collective action toward shared objectives, thus enabling efficacious action by GCS within the international polity.