School for Advanced Studies in the Social Sciences

Fear of side effects is the main motive for vaccine refusal. However, before the COVID-19 pandemic, little attention had been paid to the actual experience of adverse events and its relationship with vaccine hesitancy. This scoping review aimed to analyze the impact of VH on EAE and vice versa. We reviewed 55 articles. Most of the studies focused on COVID-19 vaccination and employed cross-sectional surveys with self-reported indicators. These studies identified significant correlations between EAE and VH. Social cognitive models shed some light on the influence of EAE on VH, while the converse is usually explained by the nocebo effect that predominately accounts for the converse. This emerging research field is hampered by significant inconsistencies in theoretical explanations, assessments of the relationship, and measurements of these two phenomena. A more comprehensive consideration of individual experience, both objective and subjective, would help develop more effective vaccine communication strategies and improve pharmacological surveillance.

Social immunity involves collective defensive strategies against infectious diseases. Despite its prevalence in eusocial insects, little is known about social immunity in non‐eusocial organisms like gregarious locusts. To address this gap, an emergent biohybrid approach bridging robotics and ethology is employed to study the behavior of the gregarious phase of Schistocerca gregaria in response to the entomopathogenic fungus Beauveria bassiana. Herein, the first animal–robot–microorganism interaction is developed to explore how infected biomimetic agents (IB) influence healthy locust behavior compared to healthy biomimetic agents (HB), as well as to infected and healthy non‐biomimetic controls (INB, HNB). Significant differences in locust responses to different agents, including latency duration, grooming behavior, tactile interactions, and aggression are observed. In healthy locusts, the increased grooming and tactile interactions in response to IB highlight potential preventive measures against pathogen transmission. Also, tactile interaction behavior is notably extended toward IB, emphasizing the role of reciprocal hygiene in limiting pathogens spread within the swarm. Infected locusts exhibit altered behaviors, including increased interaction with any robotic agents, potentially to be cleaned of fungal conidia. This animal–robot interaction study reveals social immunity dynamics in non‐eusocial organisms, with implications for pest control, evolutionary ecology, social complex systems, and bioinspired engineering design.

This article critiques the anthropological use of commoning to describe resource-sharing projects or ideals and advocates instead for a focus on socialising resources. While commoning practices involving small, autonomous communities may promote resource conservation and escape capitalist logics, they can also lead to class exclusion. In the Chinese megacity of Shenzhen, community-level cooperative companies exclude migrant outsiders, and state-encouraged commoning initiatives do not generate much solidarity between natives and migrants. Furthermore, the Chinese state’s points-based system for migrant access to public goods reflects a neoliberal logic of competition for scarce resources, creating club goods rather than truly socialised resources – social goods. Anthropologists will provide better-informed critical accounts of issues related to resource distribution if they look beyond the rhetoric of commoning and focus on the scale and degree to which resources are actually socialised.

How good are people at judging the veracity of news? We conducted a systematic literature review and pre-registered meta-analysis of 303 effect sizes from 67 experimental articles evaluating accuracy ratings of true and fact-checked false news (NParticipants = 194,438 from 40 countries across 6 continents). We found that people rated true news as more accurate than false news (Cohen’s d = 1.12 [1.01, 1.22]) and were better at rating false news as false than at rating true news as true (Cohen’s d = 0.32 [0.24, 0.39]). In other words, participants were able to discern true from false news and erred on the side of skepticism rather than credulity. We found no evidence that the political concordance of the news had an effect on discernment, but participants were more skeptical of politically discordant news (Cohen’s d = 0.78 [0.62, 0.94]). These findings lend support to crowdsourced fact-checking initiatives and suggest that, to improve discernment, there is more room to increase the acceptance of true news than to reduce the acceptance of fact-checked false news.

This article provides a reduced-order modelling framework for turbulent compressible flows discretized by the use of finite volume approaches. The basic idea behind this work is the construction of a reduced-order model capable of providing closely accurate solutions with respect to the high fidelity flow fields. Full-order solutions are often obtained through the use of segregated solvers ( solution variables are solved one after another ), employing slightly modified conservation laws so that they can be decoupled and then solved one at a time. Classical reduction architectures, on the contrary, rely on the Galerkin projection of a complete Navier–Stokes system to be projected all at once, causing a mild discrepancy with the high order solutions. This article relies on segregated reduced-order algorithms for the resolution of turbulent and compressible flows in the context of physical and geometrical parameters. At the full-order level turbulence is modeled using an eddy viscosity approach. Since there is a variety of different turbulence models for the approximation of this supplementary viscosity, one of the aims of this work is to provide a reduced-order model which is independent on this selection. This goal is reached by the application of hybrid methods where Navier–Stokes equations are projected in a standard way while the viscosity field is approximated by the use of data-driven interpolation methods or by the evaluation of a properly trained neural network. By exploiting the aforementioned expedients it is possible to predict accurate solutions with respect to the full-order problems characterized by high Reynolds numbers and elevated Mach numbers.

This pre-registered replication study explores the impact of perceived cuteness on the evolution of cultural artifacts, testing whether neotenic traits – eye size, forehead height, and head roundness – have increased in teddy bears over time. In previous research, Hinde & Barden (1980) found an increase in teddy bear neoteny while Gould (1985) found that Mickey Mouse’s features became more neotenic with time. However, both studies lacked statistical power (15 teddy bears and 3 Mickey Mouse drawings). We collected data from eight major teddy bear manufacturers over nine decades (N = 250; 1900–1980). We found that the forehead height of teddy bears significantly increased over time. Conversely, our prediction that heads became rounder and eyes became bigger were not supported. We outline four key methodological limitations that future research should address to deepen our understanding of the cultural evolution of cuteness and of cultural artifacts more broadly – i.e., sampling bias, metadata inaccuracy, categorization ambiguity, and function ambiguity.

There is strong evidence of “upcoding” whereby health care providers overstate the severity of disease to increase billing revenue. Much less is known about strategic coding in the assessment of patient eligibility for long‐term care. This paper takes advantage of a unique French linked survey dataset to document how patient assessment depends critically on the incentives of the assessing agents. I find that nursing homes assess their patients to be more disabled (thus increasing their revenue) compared to community assessors who seek to minimize disability payments levels. Public hospital‐owned long‐term care facilities are more likely to overrate disability levels; there is also evidence that cognitively impaired or socially disadvantaged patients exhibit more disability upcoding. In the context of nursing homes, upcoding might be read as “side‐coding,” driven by flaws in the assessment tool that does not allow the care provider to adequately fund the time they spend on these patients. Conversely, assessors of patients living in the community could downcode disability to shift some of the care tasks to informal caregivers.

Why do humans believe in moralizing gods? Leading accounts argue that these beliefs evolved because they help societies grow and promote group cooperation. Yet recent evidence suggests that beliefs in moralizing gods are not limited to large societies and might not have strong effects on cooperation. Here, we propose that beliefs in moralizing gods develop because individuals shape supernatural beliefs to achieve strategic goals in within-group interactions. People have a strategic interest in controlling others’ cooperation, either to extort benefits from them or to gain reputational benefits for protecting the public good. Moreover, they believe, based on their folk-psychology, that others would be less likely to cheat if they feared supernatural punishment. Thus, people endorse beliefs in moralizing gods to manipulate others into cooperating. Prosocial religions emerge from a dynamic of mutual monitoring, in which each individual, lacking confidence in the cooperativeness of conspecifics, attempts to incentivize others’ cooperation by endorsing beliefs in supernatural punishment. We show how variations of this incentive structure explain the variety of cultural attractors toward which supernatural punishment converges, including extractive religions that extort benefits from exploited individuals, prosocial religions geared toward mutual benefit, and forms of prosocial religion where belief in moralizing gods is itself a moral duty. We review evidence for nine predictions of this account and use it to explain the decline of prosocial religions in modern societies. Supernatural punishment beliefs seem endorsed as long as people believe them necessary to ensure others’ cooperation, regardless of their objective effectiveness in doing so.

In situations of poverty, do people take more or less risk? One hypothesis states that poverty makes people avoid risk, because they cannot buffer against losses, while another states that poverty makes people take risks, because they have little to lose. Each hypothesis has some previous empirical support. Here, we test the ‘desperation threshold’ model, which integrates both hypotheses. We assume that people attempt to stay above a critical level of resources, representing their ‘basic needs’. Just above this threshold, people have much to lose and should avoid risk. Below, they have little to lose and should take risks. We conducted preregistered tests of the model using survey data from 472 adults in France and the UK. The predictor variables were subjective and objective measures of current resources. The outcome measure, risk taking, was measured using a series of hypothetical gambles. Risk taking followed a V-shape against subjective resources, first decreasing and then increasing again as resources reduced. This pattern was not observed for the objective resource measure. We also found that risk taking was more variable among people with fewer resources. Our findings synthesize the split literature on poverty and risk taking, with implications for policy and interventions.

Industry 4.0 technologies radically change industrial processes. National governments have enacted innovation policies to support firms’ investments in new technologies and increase productivity growth. The Italian Industry 4.0 Plan (II4.0 Plan) was implemented with this purpose in 2017 and consisted of a horizontal fiscal plan. Using a new methodology that relies on firms’ financial accounts rather than survey data, we identify firms that benefited from the II4.0 Plan’s incentives and extend the analysis to the population of Italian firms. The results from a Difference-in-Differences regression approach show that the investments spurred by the II4.0 Plan positively affect firms’ labour productivity but heterogeneously among size classes, sectors and type of incentive. Hyper and super amortization and the credit for innovation drive the results. We frame our policy evaluation into the most recent discussion about innovation policies, raising some criticisms on the appropriateness of horizontal policies to foster digital transformation.

On December 13, 2023, Australia became the first country to ban engineered stone. This material contains more than 80 percent crystalline silica, agglomerated with resins, metal oxides and other (potentially toxic) substances. Engineered stone has become a mass-market product since the late 1990s and has contributed to a worldwide resurgence of accelerated forms of silicosis and a notable incidence of systemic diseases. Such a ban is a very rare event in a world where the regulatory framework governing the use of toxic substances in the workplace is generally limited to setting exposure limits. The Australian decision is exemplary in many respects: it is based on public consultation with all stakeholders, it contributes to updating biomedical knowledge that industries seek to conceal or undermine, and it is based on a realistic vision of real working conditions. In the absence of any evidence that lowering the silica content of this material would reduce occupational hazards related to toxic cocktail effects, this ban implements an evidence-based and precautionary public health policy.

Objective This study explored and compared stakeholder perspectives on enhancements to cervical cancer screening for vulnerable women across seven European countries. Design In a series of Collaborative User Boards, stakeholders were invited to collaborate on identifying facilitators to improve cervical cancer screening. Setting This study was part of the CBIG-SCREEN project which is funded by the European Union and targets disparities in cervical cancer screening for vulnerable women ( www.cbig-screen.eu ). Data collection took place in Bulgaria, Denmark, Estonia, France, Italy, Portugal and Romania. Participants Represented stakeholders at various levels, including user representatives (vulnerable women), healthcare professionals, social workers, programme managers and decision makers. Methods 14 meetings lasting 2 hours each were held in these seven countries between October 2021 and June 2022. The meetings were audio or video recorded, transcribed and translated into English for qualitative framework analysis. Results We engaged 120 participants in the Collaborative User Boards. Proposed solutions targeted both provider and system levels. In all countries, fostering trusting relationships between vulnerable women and social or healthcare professionals, coupled with community outreach for awareness and access to testing was a consistent recommendation. Participants in Estonia, Denmark, France, Italy, Portugal and Romania advocated for tailoring healthcare services to meet the unique needs of vulnerable populations through a holistic approach. In Bulgaria and Romania, participants advocated for the need to secure free access, from screening to follow-up, and emphasised the need for organised screening with target population screening registries. Conclusion The study offers insights into stakeholders' recommendations for enhancing cervical cancer screening services for vulnerable women across seven European countries. Despite variations in the implementation level of population-based screening programmes, the imperative to optimise outreach and proximity work to improve cervical cancer screening resonated across all countries.

To understand human practices and landscape evolution it is crucial to be able to trace evidence of past fires, notably in tropical environments. In such anthromes, phytoliths are generally well preserved and provide local signals on the environment. However, the different approaches to identifying burnt or heated phytoliths have proved inadequate. The recent investigation of auto-fluorescent phytoliths as proxy indicators of fire opens up new possibilities, however such studies have so far been limited to European temperate regions. The present contribution further explores the potential of this technique, attempting to reconstruct fire histories in tropical and subtropical latitudes. Therefore, we investigated various modern and ancient contexts in Guatemala, Senegal and the Canary Islands using descriptive and quantitative approaches to fluorescence. This comparative process revealed a diversity of fluorescence responses depending on the ecosystems studied, with anthropized areas often producing more fluorescent phytoliths. These results were obtained despite the use of different extraction and mounting methods. In contrast, coloured phytoliths, often considered an indicator of environmental burning, proved not very informative in some of the samples. This study reinforces our conviction that the auto-fluorescence of phytoliths is a universal phenomenon and is useful as a new proxy for detecting ancient fire in tropical and subtropical archaeological and palaeoenvironmental deposits.

Income maps have been extensively used for identifying populations vulnerable to global changes. The frequency and intensity of extreme events are likely to increase in coming years as a result of climate change. In this context, several studies have hypothesized that the economic and social impact of extreme events depend on income. However, to rigorously test this hypothesis, fine‐scale spatial income data is needed, compatible with the analysis of extreme climatic events. To produce reliable high‐resolution income data, we have developed an innovative machine learning framework, that we applied to produce a European 1 km‐gridded data set of per capita disposable income for 2015. This data set was generated by downscaling income data available for more than 120,000 administrative units. Our learning framework showed high accuracy levels, and performed better or equally than other existing approaches used in the literature for downscaling income. It also yielded better results for the estimation of spatial inequality within administrative units. Using SHAP values, we explored the contribution of the model predictors to income predictions and found that, in addition to geographic predictors, distance to public transport or nighttime light intensity were key drivers of income predictions. More broadly, this data set offers an opportunity to explore the relationships between economic inequality and environmental degradation in health, adaptation or urban planning sectors. It can also facilitate the development of future income maps that align with the Shared Socioeconomic Pathways, and ultimately enable the assessment of future climate risks.

Context There are urgent calls to transition society to more sustainable trajectories, at scales ranging from local to global. Landscape sustainability (LS), or the capacity for landscapes to provide equitable access to ecosystem services essential for human wellbeing for both current and future generations, provides an operational approach to monitor these transitions. However, the complexity of landscapes complicates how and what to consider when assessing LS. Objectives To identify important features of landscapes that remain challenging to consider in LS assessments and provide guidance to strengthen future assessments. Methods We conducted two workshops to identify the complex features of landscapes that remain under-considered in LS assessments, and developed guidelines on how to better incorporate these features. Results We identify open and connected boundaries and diversity of values as landscape features that must be better considered in LS assessments or risk exacerbating offstage sustainability burdens and power inequalities. We provide guidelines to avoid these pitfalls which emphasize assessing ecosystem service interactions across interconnected landscapes and incorporating local actors’ diverse values. Conclusions Our guidelines provide a stepping stone for researchers and practitioners to better incorporate landscape complexities into LS assessments to inform landscape-level decisions and actions.

Science is crucial for evidence-based decision-making. Public trust in scientists can help decision makers act on the basis of the best available evidence, especially during crises. However, in recent years the epistemic authority of science has been challenged, causing concerns about low public trust in scientists. We interrogated these concerns with a preregistered 68-country survey of 71,922 respondents and found that in most countries, most people trust scientists and agree that scientists should engage more in society and policymaking. We found variations between and within countries, which we explain with individual- and country-level variables, including political orientation. While there is no widespread lack of trust in scientists, we cannot discount the concern that lack of trust in scientists by even a small minority may affect considerations of scientific evidence in policymaking. These findings have implications for scientists and policymakers seeking to maintain and increase trust in scientists.