This study analyzes empirically and graphically the effects of the relative market price level on the premiums and discounts received associated with alfalfa hay quality. Findings indicate that at times when alfalfa prices are elevated relative to the average, there is no significant impact on the average premiums and discounts received. Conversely, at times when alfalfa prices are depressed relative to the average, there are statistically significant variations in the premiums and discounts across quality grades compared with a market characterized by average prices. Understanding these dynamics can aid producers in optimizing production decisions and assist consumers in managing input costs.

In recent years, virtue epistemology has been criticized for its individualism. Correspondingly, some attempts have been made to make it more social. However, there is some confusion about what it means for virtue epistemology to be individualistic, and how it should be socialized in the face of this. The current paper proposes a systematic answer to these questions. We distinguish elements of theories of virtue that might give rise to different forms of individualism: “subject individualism,” “faculty/trait individualism,” and “value individualism.” Then we show what specific challenges these elements might pose for virtue reliabilism and responsibilism. We focus on two challenges: the epistemic value of other-regarding intellectual virtues, and the problem of “epistemic outsourcing.” In both cases, we identify and evaluate possible strategies for socializing these elements of virtue epistemology.

Jubilees are good to think with, obviously. They provide a fitting opportunity to look back, to take stock, and to offer some thoughts about the future. As a scholar working on Byzantine history (and only slightly older than BMGS at that) I recognize that the state of the field has changed immensely in the last fifty years. First, there was a major expansion in departments and programmes dedicated to Byzantine studies, followed more recently by a contraction. And yet, even while Byzantine studies are offered in fewer academic institutions, there is an immense proliferation of academic research and publications on the Byzantine Empire – trend accelerating. Exact numbers may be hard to come by, but a quick search on WorldCat for books published in 2023 with the word ‘Byzantine’ in the title brought forth almost two hundred books – in English alone. If we add journal articles (there are over twenty major journals devoted solely to Byzantine studies), chapters in edited volumes, and, especially publications in languages other than English, we would probably reach the low thousands, all in one year. To survey, much less to read with care and absorb all this new knowledge, has become impossible. How handy would it be if someone else took over this task for us – processing research and synthesizing it in a clear, concise and readable volume. It is highly doubtful that such a book could be produced today, but there is a work that fulfilled these functions for a very long time, one of the most cited and recommended textbooks in Byzantine history, Georg Ostrogorsky's History of the Byzantine State.

The Brahman sage Gautama cursed Indra with emasculation, in some versions through the appearance of vulvas on his body, as a punishment for intercourse with Gautama's wife, Ahalyā; Ahalyā's punishment involved detraction from her visible or physical presence. I present an analysis of the version as told in Padmapurāṇa 1.54. The story, in addition to reflecting male suspicion of women and dread of feminisation, simultaneously functions as a cautionary tale about the dangers of succumbing to lust and reflects inter-varṇa tension: the weak-willed Indra, a divine kṣatriya, is humiliated by the continent Gautama, whose asceticism is the source of the devastating power that he unleashes against both Indra and Ahalyā. I also compare this myth to the Greek tales of Achilles, Herakles, and Teiresias's feminisations, and suggest that the association of heroic feminisation with sexuality (as seen in the stories in which Indra, Achilles, and Herakles are feminised) may be a shared inheritance from Proto-Indo-European times. However, the myths of Achilles and Herakles's feminisations, like that of Indra's, are shaped by their specific cultural context: the feminised Greek heroes’ penetration of women is confirmation of their continued masculinity, rather than the result of a reprehensible lack of self-control.

Many influential political science articles use close elections to study how important outcomes vary after a certain type of candidate wins, such as a Democrat or a Republican. This politician characteristic regression discontinuity (PCRD) design offers opportunities for inferential leverage but also the potential for confusion. In this article, we clarify what causal claims the PCRD licenses, offering a rigorous causal analysis that points to three principal lessons. First, PCRDs do nothing to isolate the effect of the politician characteristic of interest as apart from other politician characteristics. Second, selection processes (regarding both “who runs” and “which elections are close”) can generate and exacerbate such confounding, as noted in Marshall (2024). Third and more fortunately, this approach does make it possible to estimate the average effect of electing a leader of type “A” vs. “B” in the context of close elections, treating the units as districts, not leaders. We also suggest a set of tools that can aid in falsifying key assumptions, avoiding unwarranted claims, and surfacing mechanisms of interest. We illustrate these issues and tools through a reanalysis of an influential study about what happens when extremists win primaries (Hall 2015).

Machine-learning (ML) methods have shown great potential for weather downscaling. These data-driven approaches provide a more efficient alternative for producing high-resolution weather datasets and forecasts compared to physics-based numerical simulations. Neural operators, which learn solution operators for a family of partial differential equations, have shown great success in scientific ML applications involving physics-driven datasets. Neural operators are grid-resolution-invariant and are often evaluated on higher grid resolutions than they are trained on, i.e., zero-shot super-resolution. Given their promising zero-shot super-resolution performance on dynamical systems emulation, we present a critical investigation of their zero-shot weather downscaling capabilities, which is when models are tasked with producing high-resolution outputs using higher upsampling factors than are seen during training. To this end, we create two realistic downscaling experiments with challenging upsampling factors (e.g., 8x and 15x) across data from different simulations: the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) and the Wind Integration National Dataset Toolkit. While neural operator-based downscaling models perform better than interpolation and a simple convolutional baseline, we show the surprising performance of an approach that combines a powerful transformer-based model with parameter-free interpolation at zero-shot weather downscaling. We find that this Swin-Transformer-based approach mostly outperforms models with neural operator layers in terms of average error metrics, whereas an Enhanced Super-Resolution Generative Adversarial Network-based approach is better than most models in terms of capturing the physics of the ground truth data. We suggest their use in future work as strong baselines.

We present a family of minimal modal logics (namely, modal logics based on minimal propositional logic) corresponding each to a different classical modal logic. The minimal modal logics are defined based on their classical counterparts in two distinct ways: (1) via embedding into fusions of classical modal logics through a natural extension of the Gödel–Johansson translation of minimal logic into modal logic S4; (2) via extension to modal logics of the multi- vs. single-succedent correspondence of sequent calculi for classical and minimal logic. We show that, despite being mutually independent, the two methods turn out to be equivalent for a wide class of modal systems. Moreover, we compare the resulting minimal version of K with the constructive modal logic CK studied in the literature, displaying tight relations among the two systems. Based on these relations, we also define a constructive correspondent for each minimal system, thus obtaining a family of constructive modal logics which includes CK as well as other constructive modal logics studied in the literature.

Bilinguals use languages strategically and make decisions differently depending on the language context. Here, we explored whether verbal feedback modulates language use and risk-taking in bilinguals engaged in a coin-drawing game that incentivises lying. In the game, participants announced bets in Chinese or English, and feedback on the outcome of the current bet was given in the same language. They selected Chinese over English after receiving positive feedback in Chinese, and no language difference was found when feedback was provided in English. They also tended to take more risks after receiving positive than negative feedback. Furthermore, participants were more likely to switch from one language to the other following negative feedback as compared to positive feedback, and when telling the truth, they were faster after negative than positive feedback. Thus, the language in which bilinguals receive feedback constrains language use, which may have implications for understanding interactions in multilingual communities.

In today’s insurance market, numerous cyber insurance products provide bundled coverage for losses resulting from different cyber events, including data breaches and ransomware attacks. Every category of incident has its own specific coverage limit and deductible. Although this gives prospective cyber insurance buyers more flexibility in customizing the coverage and better manages the risk exposures of sellers, it complicates the decision-making process in determining the optimal amount of risks to retain and transfer for both parties. This article aims to build an economic foundation for these incident-specific cyber insurance products with a focus on how incident-specific indemnities should be designed for achieving Pareto optimality for both the insurance seller and the buyer. Real data on cyber incidents are used to illustrate the feasibility of this approach. Several implementation improvement methods for practicality are also discussed.