Normative conflict is at the centre of many current discussions about order and change in world politics. In this article, we argue that studying normativity in practice is necessary when analysing processes of global ordering, such as negotiating, cooperating, or protesting. Practices are imbued with normativity. This key aspect, however, remains often overlooked in current International Relations (IR) practice research due to a conservative bias that treats practices mainly as patterned. Focusing on normativity reveals the inherent contestation of practices, providing a conceptual avenue for understanding how international practices oscillate between social order and change. Normativity can be defined as evaluating criteria experienced in practice and used for the contextualised moral judgement of public performances. This perspective is relevant for IR scholars interested in how relational, contested, and learning processes relate to order and ordering in world politics. We propose taking a comprehensive approach hereto based on three key dimensions: how normativity is enacted and disputed in practice; how it must be learnt as practical knowledge in communities; and, how ambiguity remains due to the multiplicity of rules applied in everyday situations. We illustrate our approach by examining global protests in different fields (sports, the environment, and peace).

This article explores the causes of nationalist civil war, a subtype of ethnic civil war in which anti-state actors fight for greater communal autonomy. It presents a theoretical framework claiming that grievances over lost communal autonomy commonly motivate nationalist civil war, but that other conditions are needed to put this motive into action: Nationalist frames and expectations must make communities sensitive to lost autonomy, and mobilizational resources must be available so actors can organize nationalist movements. Nation-state building, in turn, commonly promotes reductions in communal autonomy, and British colonial pluralism frequently strengthened nationalist frames, expectations, and mobilizational resources, suggesting that nationalist civil war should be common in former British colonies after transitions from empire to nation-state. To test the framework, this article provides a comparative historical analysis of Zomia, a region that has the highest concentration of nationalist civil wars in the world and in which half of the countries are former British colonies. The analysis provides strong evidence supporting the theoretical framework.

Narrow bracketers who are myopic in specific decisions would fail to consider preexisting risks in investment and neglect hedging opportunities. Growing evidence has demonstrated the relevance of narrow bracketing. We take a step further in empirical investigation and study individual heterogeneity in narrow bracketing. Specifically, we use a lab experiment in investment and hedging that elicits subjects’ preferences on rich occasions to uncover the individual degree of narrow bracketing without imposing distributional assumptions. Combining prospect theory and narrow bracketing can explain our findings: Subjects who invest more also insure more, and subjects insure significantly less in the loss domain than in the gain domain. More importantly, we show that the distribution of the individual degree of narrow bracketing is skewed at two extremes, yet with a substantial share of people in the middle who partially suffer from narrow bracketing. Neglecting this aspect, we would overestimate the severity of narrow bracketing and misinterpret its relation with individual characteristics.

We study the length of short cycles on uniformly random metric maps (also known as ribbon graphs) of large genus using a Teichmüller theory approach. We establish that, as the genus tends to infinity, the length spectrum converges to a Poisson point process with an explicit intensity. This result extends the work of Janson and Louf to the multi-faced case.

Research on individual decisions from experience reveals a robust tendency to behave as if rare events are underweighted. Experimental studies of strategic interactions often exclude probabilistic outcomes, thus neglecting the potential extension of this tendency to strategic games. Our study addresses this gap by examining how players in games adjust their strategies when confronted with low-probability, high-impact outcomes. We introduce two finitely repeated, asymmetric games with lottery-based payoffs. These games, when simplified by replacing lotteries with their expected values, yield straightforward equilibrium predictions based on dominant strategies. However, results from three experiments reveal players strongly deviate from these predictions, instead behaving consistently with underweighting of rare events. The results additionally indicate that social preferences also play a role in shaping behavior. To explain these observations, we propose the simplistic Reciprocal Altruistic Sampler (REALS) model. This model posits that players’ decisions are a result of the interplay between reliance on small samples of past experiences, altruistic tendencies, and strategic considerations. We experimentally compare behavior in variants of the games that disentangle the behavior to these three components, and show that the REALS model, despite its simplicity, effectively captures their complex interactions. Our results additionally demonstrate that players can often choose strictly dominated strategies in a sophisticated effort to react to underweighting of rare events by other players. Overall, this study enhances our understanding of strategic decision making by highlighting the crucial impact of rare events and the interplay of different uncertainties in influencing players’ choices.

In reflecting on the history of Management and Organization Review (MOR), it is not cliché to say that ‘time flies’. It is amazing that MOR has been in existence for 20 years. The memories of the excitement, challenges, and anxiety in the founding years are still vivid, like yesterday. Most organizations die within 5 years of their birth (Daepp, Hamilton, West, & Bettencourt, 2015; Gürtler & Miller, 2022; SAIC, 2013). We can assume that MOR has passed its survival threat. What accounts for its survival success? Is it luck, as would be the case of some entrepreneurial ventures that came to be at the right time in the right place? Survival was not on the minds of the founders of MOR; making an impact on advancing Chinese management research was. What were the founders' aspirations for creating a new journal in an already highly competitive and mature field of journal publishing in business and management? How well has MOR reached its aspirations? Twenty years is a good occasion to take stock of the achievements of MOR, its challenges and opportunities, and what future does it desire in serving the global community of Chinese management and organization scholars?

Glacier ice flux is a key indicator of mass balance; therefore, accurate monitoring of ice dynamics is essential. Satellite-based methods are widely used for glacier velocity measurements but are limited by satellite revisit frequency. This study explores using seismic station internal GPS data to track glacier movement. While less accurate than differential GPS, this method offers high-temporal resolution as a by-product where seismic stations are deployed. Using a seismic station on Borebreen, Svalbard, we show that internal GPS provides reliable surface velocity measurements. When compared with satellite-inferred velocities, the results show a strong correlation, suggesting that the internal GPS, despite its inherent uncertainty, can serve as an efficient tool for glacier velocity monitoring. The high-temporal sampling reveals short-term dynamics of speed-up events and underscores the role of meltwater in driving these processes. This approach augments glacier observation networks at no additional cost.

Photovoltaic (PV) energy grows rapidly and is crucial for the decarbonization of electric systems. However, centralized registries recording the technical characteristics of rooftop PV systems are often missing, making it difficult to monitor this growth accurately. The lack of monitoring could threaten the integration of PV energy into the grid. To avoid this situation, remote sensing of rooftop PV systems using deep learning has emerged as a promising solution. However, existing techniques are not reliable enough to be used by public authorities or transmission system operators (TSOs) to construct up-to-date statistics on the rooftop PV fleet. The lack of reliability comes from deep learning models being sensitive to distribution shifts. This work comprehensively evaluates distribution shifts’ effects on the classification accuracy of deep learning models trained to detect rooftop PV panels on overhead imagery. We construct a benchmark to isolate the sources of distribution shifts and introduce a novel methodology that leverages explainable artificial intelligence (XAI) and decomposition of the input image and model’s decision regarding scales to understand how distribution shifts affect deep learning models. Finally, based on our analysis, we introduce a data augmentation technique designed to improve the robustness of deep learning classifiers under varying acquisition conditions. Our proposed approach outperforms competing methods and can close the gap with more demanding unsupervised domain adaptation methods. We discuss practical recommendations for mapping PV systems using overhead imagery and deep learning models.

In this work, we studied the broadband temporal and spectral properties of the flat-spectrum radio quasar Ton 599. We collected the long-term data from January 2019 to August 2024 when the source was in a long flaring episode. We used the Bayesian block methodology to identify the various flux states, including three flares. The broadband fractional variability is estimated during two flaring states. The F$_{\text{var}}$ variation with respect to frequency shows a nearly double hump structure similar to broadband SED. The power spectral density shows a pink-noise kind of stochastic variability in the light curve, and we do not see any break in the power spectrum, suggesting a much longer characteristic timescale is involved in gamma-ray variability. The flux distribution is well-fitted with a double log-normal flux distribution, suggesting the variability of non-linear in nature. The gamma-ray, optical, and X-ray emissions were found to be highly correlated with a zero time lag, suggesting a co-spatial origin of their emissions. We used the one-zone leptonic model to reproduce the broadband spectrum in the energy range from the IR to very high-energy gamma rays. The increase in the magnetic field and the Doppler factor were found to be the main causes for high flux states. The XMM-Newton spectra taken during one of the flaring durations exhibit a signature of thermal black body emission from the accretion disc, suggesting a possible disc-jet coupling. This has also been indicated by the gamma-ray flux distribution, which shows the distribution as non-linear in nature, which is mostly seen in galactic X-ray binaries or active galactic nuclei, where the accretion disc dominates the emission.