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Scholars from a range of disciplines including medicine, sociology, psychology, and philosophy have addressed the concepts of ambiguity and uncertainty in medical practice and training. Most of this scholarship has been descriptive, focusing on defining and measuring ambiguity and uncertainty tolerance or tracking clinicians’ responses to ambiguous and uncertain situations. Meanwhile, scholars have neglected some fundamental normative questions: Is tolerance of uncertainty good; if so, to what extent? Using a philosophical approach to these questions, we show that neither tolerance nor intolerance of uncertainty is necessarily a good or bad trait. Rather, both tolerance and intolerance of uncertainty can give physicians advantages while at the same time exposing them to pitfalls in clinical practice. After making this case, we argue that cultivating certain virtues—like courage, diligence, and curiosity—could help clinicians avoid the dangers of excessive tolerance and intolerance of uncertainty. Finally, we suggest that medical educators develop curricula and career counseling beginning with matriculation and proceeding through specialty choice and residency training that explicitly address trainees’ responses to clinical uncertainty. These programs should encourage trainees, students and residents, to be mindful of their reactions to uncertainty and help them develop virtues that will allow them to avoid the hazards of extreme tolerance or intolerance of uncertainty.

Young people experience different treatment compared to older adults in the English welfare and homelessness systems, encountering varying levels of protection and disadvantage. This paper uses a value-pluralist perspective to explore the normative rationales for and the ethical defensibility of these policy differences. Evidence from 38 key informant interviews suggests that the English homelessness system is shifting towards a vulnerability-oriented response to young people. But an inconsistent value framework within the welfare system systematically disadvantages them without offering a corresponding degree of protection. As such, these closely-connected areas of social policy pull in opposing directions. Although individual positions targeting young people may (to greater and lesser extents) be justifiable, this disparity in values creates an incoherent and indefensible welfare policy landscape for this group.

In fetal alcohol spectrum disorders (FASD), brain growth deficiency is a hallmark of subjects with both fetal alcohol syndrome (FAS) and nonsyndromic FASD (NS‐FASD, that is, those without specific diagnostic features). Although previous studies have suggested that the deep grey matter is heterogeneously affected at the group level, it has not yet been established within proper scaling modeling, nor has it been given a place in the FASD diagnostic criteria where neuroanatomical features still contribute almost nothing to diagnostic specificity. We segmented a 1.5T T1‐weighted brain MRI dataset of 90 monocentric FASD patients (53 FAS, 37 NS‐FASD) and 95 typically developing controls (ages 6–20), using volBrain‐vol2Brain as reference, and both Freesurfer‐SAMSEG and FSL‐FIRST to estimate result robustness. The segmentation resulted in seven anatomical volumes: total brain (TBV), total deep grey matter, caudate, putamen, globus pallidus, thalamus, and accumbens. After adjusting for confounds, we fitted the scaling relationship between deep grey matter nuclei volumes (Vi) and TBV (Vi = b × TBVa) and evaluated the effect of FAS on scaling. We then estimated the volumetric deviation from typical scaling (vDTS) for each deep grey nucleus volume in the FAS sample. Finally, we tested the improvement of FAS versus control classifiers based on total deep grey matter vDTS or total brain deviation from typical volume, by adding the five nuclear vDTS, both in terms of performance and generalizability to NS‐FASD. Scaling was significantly different between the FAS and control groups for all deep grey matter nuclei (p < 0.05). We confirmed the undersizing of total deep grey matter in FAS (vDTS = −6%) and identified a pattern of volumetric undersizing, most pronounced in the caudate (−13%) and globus pallidus (−11%), less so in the thalamus (−4%) and putamen (−2%) and sparing the accumbens (0%). These findings were consistent across segmentation tools, despite variations in magnitude. The pattern‐based classifier was more efficient than the one based on total deep grey matter alone (p < 0.001) and identified 32.4% of the NS‐FASD as having a FAS‐like deep grey matter phenotype, compared to 18.9% with the classifier based on total deep grey matter alone (p = 0.113). Added to a classifier based on TBV only, the pattern improved the performance (p = 0.033) of the model and increased identification of NS‐FASD with a FAS‐like neuroanatomical phenotype from 37.8% to 62.2% (p = 0.002). This study details the volumetric undersizing of deep grey matter in a large series of FASD patients. It reveals a differential pattern of vulnerability to prenatal alcohol exposure partially convergent across automatic segmentation tools. It also strongly suggests that this pattern of volumetric undersizing in the deep grey matter may contribute to a neuroanatomical signature of FAS that is usable to improve the probabilistic diagnosis of NS‐FASD by means of MRI‐based diagnostic classifiers. Using MRI‐based normative scaling analysis, we identified a robust pattern of deep grey matter undersizing in fetal alcohol syndrome (FAS). This novel neuroanatomical marker boosted the performances of brain size‐based classifiers and their generalizability to fetal alcohol spectrum disorders lacking FAS‐specific clinical features, supporting its use to improve diagnostic reliability.

BackgroundThe location of the hemorrhagic of spontaneous intracerebral hemorrhage (sICH) is clinically pivotal for both identifying its etiology and prognosis, but comprehensive and quantitative modeling approach has yet to be thoroughly explored.MethodsWe employed lesion-symptom mapping to extract the location features of sICH. We registered patients’ non-contrast computed tomography image and hematoma masks with standard human brain templates to identify specific affected brain regions. Then, we generated hemorrhage probabilistic maps of different etiologies and prognoses. By integrating radiomics and clinical features into multiple logistic regression models, we developed and validated optimal etiological and prognostic models across three centers, comprising 1162 sICH patients.ResultsHematomas of different etiology have unique spatial distributions. The location-based features demonstrated robust classification of the etiology of spontaneous intracerebral hemorrhage (sICH), with a mean area under the curve (AUC) of 0.825 across diverse datasets. These features provided significant incremental value when integrated into predictive models (fusion model mean AUC = 0.915), outperforming models relying solely on clinical features (mean AUC = 0.828). In prognostic assessments, both hematoma location (mean AUC = 0.762) and radiomic features (mean AUC = 0.837) contributed substantial incremental predictive value, as evidenced by the fusion model’s mean AUC of 0.873, compared to models utilizing clinical features alone (mean AUC = 0.771).ConclusionsOur results show that location features were more intrinsically robust, generalizable relative, strong interpretability to the complex modeling of radiomics, our approach demonstrated a novel interpretable, streamlined, comprehensive etiologic classification and prognostic prediction framework for sICH.

Access to healthcare for refugees is often contextually and conceptually diverse. This study set out to evaluate the efficiency of the healthcare services provided for Syrian refugees in Turkey and other refugee response and resilience plan (3RP) states. Data envelopment analysis is utilized for efficiency analysis using primary healthcare system indicators. Efficiency is broken down into pure technical efficiency and scale efficiency to identify causes of inefficiency. Normative analysis is used to employ a teleological approach to better understand current refugee healthcare policies. The findings show a decline in the overall efficiency for Turkey and other 3RP states. However, Turkey’s operational practices could be a model for other 3RP states due to its relatively high pure technical efficiency. Scale inefficiency negatively impacts the overall efficiency of Turkey’s service, while other 3RP states exhibit a rather consistent performance. The study concludes that Turkey’s healthcare system for refugees is inefficient, resulting in inadequate access for Syrian refugees. As such, operational and scale efficiency must be synergized for Turkey to fulfill its obligation to provide adequate healthcare for Syrian refugees. Additionally, COVID-19 was found to have exacerbated the challenges Syrian refugees face accessing healthcare. Policy recommendations have been made in line with the findings of the study.

Allocating fish quota is a hotly disputed issue across the world, and many different criteria have been employed to achieve it. However, little attention has been devoted to examining the fairness of those criteria. This study aims to fill this gap by focusing on the eight most prominent criteria that have been used or proposed—prior use; market forces; historical entitlement; geographical proximity; sovereign right; economic dependence; environmental stewardship; and equal shares—and examining their respective ethical credentials as principles of distributive justice. The assumption lying behind this aim is that if agreement can be reached on which criteria are the fairest, future conflicts over quota allocations might be averted. The method used to conduct this research was normative analysis, and the materials analysed were obtained from databases such as the Web of Science. However, the study found that the ethically strongest criteria are environmental stewardship and economic dependence, but the most prevalent criteria are historical entitlement and geographical proximity (zonal attachment). So, the principles of distributive justice that are most likely to be applied are not the fairest principles but the principles with the greatest political support. For some commentators, this signifies that justice and ethics have been sacrificed to power and politics. However, there is some evidence that the tide is turning and the arguments in favour of fairness, perhaps in hybrid forms, are beginning to gain momentum.

The relevance of tax progressivity measures to policymaking depends on whether they help assess the extent to which taxation leads to social welfare gains or losses. The social welfare implications of progressivity measures have yet to be explored adequately in the literature. This paper helps to fill this gap by proposing a social welfare function framework to derive measures of tax progressivity and explore their normative properties. Using the social welfare framework, the paper derives the Kakwani index from Sen’s social welfare function as well as a new class of progressivity measures that incorporate a distributional judgment parameter capturing inequality aversion. The paper also discusses the social welfare implications of the Suits measure of tax progressivity and develops a new measure of tax progressivity derived from the Bonferroni social welfare function. The paper derives both relative and absolute measures of tax progressivity from the social welfare function framework. The methodology developed in the paper is applied to make international comparisons of tax progressivity in 32 developed countries. The paper calculates the magnitude of welfare gains and losses due to taxation and the required social rates of return of public investments for governments to break even. This paper finds that the governments in some countries have to generate high social rates of return from their public investments to compensate for losses of social welfare from taxation. It concludes that optimizing social welfare requires designing a progressive tax system, minimizing the administrative costs of collecting taxes, and maximizing the social rates of return by efficiently investing tax revenues.

Neuro-oncology research is broad and includes several branches, one of which is neuroimaging. Magnetic resonance imaging (MRI) is instrumental for the diagnosis and treatment monitoring of patients with brain tumors. Most commonly, structural and perfusion MRI sequences are acquired to characterize tumors and understand their behaviors. Thanks to technological advances, structural brain MRI can now be transformed into a so-called average brain accounting for individual morphological differences, which enables retrospective group analysis. These normative analyses are uncommonly used in neuro-oncology research. Once the data have been normalized, voxel-wise analyses and spatial mapping can be performed. Additionally, investigations of underlying connectomics can be performed using functional and structural templates. Additionally, a recently available template of spatial transcriptomics has enabled the assessment of associated gene expression. The few published normative analyses have shown relationships between tumor characteristics and spatial localization, as well as insights into the circuitry associated with epileptogenic tumors and depression after cingulate tumor resection. The wide breadth of possibilities with normative analyses remain largely unexplored, specifically in terms of connectomics and imaging transcriptomics. We provide a framework for performing normative analyses in oncology while also highlighting their limitations. Normative analyses are an opportunity to address neuro-oncology questions from a different perspective.

Introducción/objetivo: la sociedad requiere que los esfuerzos en CTI no sólo apunten al crecimiento económico, sino que promuevan la conservación del medio ambiente y la justicia social (la transformación hacia la sostenibilidad). En este sentido, se requiere la construcción de sistemas de innovación orientados a la sostenibilidad (SIS); es decir, que tengan la capacidad de direccionar la transformación de los sistemas sociotécnicos. Este artículo de perspectiva desarrolla una aproximación teórico-práctica para la implementación de sistemas de innovación que incluya las dimensiones de normatividad (direccionalidad) y exploración, que son necesarias para operar tales procesos de transformación. Metodología: el análisis de sistemas y el análisis de decisiones fueron usados como estructura para organizar conceptos y métodos de diferentes corrientes de pensamiento, los cuales fueron sintetizados en este trabajo con el propósito funcional de desarrollar una herramienta en capacidad de proveer a los sistemas de innovación de las dimensiones de normatividad y exploración. Resultados: cuando hablamos de desarrollo sostenible y usamos el concepto de sostenibilidad estamos necesariamente dando una direccionalidad a los sistemas de innovación. Operacionalizar esta función requiere conjugar un análisis normativo —orientado a construir una visión de un futuro sostenible para los actores participantes en el sistema de innovación—, y un análisis exploratorio enfocado en identificar las rutas de transformación con mayor potencial de alcanzar el futuro deseado. Este enfoque metodológico, construido a partir de varias aproximaciones empíricas, es aquí denominado análisis integrado de futuros. Conclusión: este trabajo describe una perspectiva sintética y pragmática para la implementación de SIS. Esta perspectiva es una guia para equipos consultores en su tarea de apoyar a actores y tomadores de decisión en el proceso de formalización/fortalecimiento de estos sistemas, y en la identificación e implementación de los cursos de acción más apropiados para su implementación. ABSTRACT Introduction: In contemporary society, there is a growing expectation for STI efforts to go beyond economic growth and actively contribute to environmental protection and social justice (transformation towards sustainability). To meet this demand, it is necessary to construct innovation systems that are specifically oriented towards sustainability, facilitating the transformation of sociotechnical systems. This perspective article presents a comprehensive framework that combines theoretical and practical perspectives for implementing innovation systems, incorporating the essential elements of normativity (directionality) and exploration required to drive such transformative processes. Methodology: We formulated a methodological approach that provides innovation systems with normative and exploratory dimensions by synthesizing concepts and methods from several schools of thought, using Systems Analysis and Decision Analysis as conceptual frameworks. Results: Within the context of sustainable development, the principles of sustainability serve as the guiding framework for innovation systems. To successfully implement this approach, it is crucial to integrate both normative analysis, which emphasizes the construction of a shared vision among stakeholders within the innovation system, and exploratory analysis, which aims to identify the most viable transformation pathways for realizing the desired future. Our proposed methodological perspective, referred to as Integrated Futures Analysis, is a step-by-step generalization built upon a synthesis of empirical approaches that combines normative and exploratory analysis. This approach aims to facilitate the understanding and implementation of sustainability-oriented innovation systems. Conclusion: In this article, a synthetic and pragmatic approach to implementing sustainability-oriented innovation systems (SIS) was introduced. The perspective outlined in this article can be effectively employed by consultant teams to aid stakeholders and decision-makers in formalizing and enhancing SIS. Additionally, it helps in identifying the most appropriate actions and methods for implementation of SIS.

What, if anything, is wrong with high executive compensation? Is the common \"lay reaction\" of indignation and moral outrage justified? In this paper, my main goal is to articulate in a more systematic and philosophical manner the egalitarian responses to these questions. In order to do so, I suggest that we take some insights from recent debates on two versions of egalitarianism: a distributive one, according to which no one should be worse off than others because of unfair distributions of goods and resources, especially ones based on matters of luck or arbitrary factors, and a relational one, which maintains that egalitarian justice requires members of a society to relate to one another as equals. Drawing on recent attempts to highlight the tricky nature of managerial authority, I argue that high inequalities in pay are not simply a distributional matter but should also be analyzed through a relational lens. I also attempt to show that relational egalitarians are well-equipped to question the now dominant \"incentives\" view of CEO compensation.