Addressing collective action problems requires individuals to engage in coordinated and cooperative behaviours. Existing research suggests that individuals' propensity to work together depends in part on their belief that others support the cause in question. People form their expectations about prevalent beliefs and behaviours from many sources. To date, most of the literature has focussed on how social norm perceptions are inferred from peers or summary statistics. We explore an understudied source of norm information: the passage of policies by democratically elected institutions. Institutional signals, such as the setting of defaults, national laws or policies, can act as coordination devices, signalling or prescribing social norms to large audiences. However, their expressive function is likely to depend on whether the institution is seen as accountable to the public. In two highly powered, pre-registered experiments ( = 11 636), we examine the role of policy signals as a source of social norm information. In Study 1, Americans randomly assigned to learn that their state passed a 100% renewable energy mandate believe that a greater percentage of their state's residents support such a mandate. In Study 2, we replicate this effect for national policy and show that the influence is moderated by information about whether the government represents the will of the people. This article is part of the theme issue 'Social norm change: drivers and consequences'.
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http://dx.doi.org/10.1098/rstb.2023.0038 | DOI Listing |
Phys Rev Lett
December 2024
California Institute of Technology, Division of Chemistry and Chemical Engineering, Pasadena, California 91125, USA.
We introduce a change of perspective on tensor network states that is defined by the computational graph of the contraction of an amplitude. The resulting class of states, which we refer to as tensor network functions, inherit the conceptual advantages of tensor network states while removing computational restrictions arising from the need to converge approximate contractions. We use tensor network functions to compute strict variational estimates of the energy on loopy graphs, analyze their expressive power for ground states, show that we can capture aspects of volume law time evolution, and provide a mapping of general feed-forward neural nets onto efficient tensor network functions.
View Article and Find Full Text PDFUnderstanding how the collective activity of neural populations relates to computation and ultimately behavior is a key goal in neuroscience. To this end, statistical methods which describe high-dimensional neural time series in terms of low-dimensional latent dynamics have played a fundamental role in characterizing neural systems. Yet, what constitutes a successful method involves two opposing criteria: (1) methods should be expressive enough to capture complex nonlinear dynamics, and (2) they should maintain a notion of interpretability often only warranted by simpler linear models.
View Article and Find Full Text PDFAm J Geriatr Psychiatry
January 2025
Division of Geriatrics and Palliative Medicine (PK), Weill Cornell Medicine, New York, NY, USA.
Objective: To test the efficacy of Problem Adaptation Therapy for Pain (PATH-Pain) versus Usual Care (UC) in reducing pain-related disability, pain intensity, and depression among older adults with chronic pain and negative emotions.
Design: RCT assessing the between-group differences during the acute (0-10 weeks) and follow-up (weeks 11-24) phase of treatment.
Setting: A geriatrics primary care site.
J Deaf Stud Deaf Educ
January 2025
Institute of Neurology of Senses and Language, Hospital of St. John of God Linz, Linz, Austria.
Language comprehension is an essential component of human development that is associated not only with expressive language development and knowledge acquisition, but also with social inclusion, mental health, and quality of life. For deaf and hard-of-hearing adults with intellectual disability, there is a paucity of measures of receptive sign language skills, although these are a prerequisite for individualized planning and evaluation of intervention. Assessments require materials and procedures that are accurate, feasible, and suitable for low levels of functioning.
View Article and Find Full Text PDFGenes (Basel)
January 2025
Division of Cancer Prevention and Genetics, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.
Women carrying pathogenic/likely pathogenic (P/LP) variants in moderate- or high-penetrance genes have an increased risk of developing breast cancer. However, most P/LP variants associated with breast cancer risk show incomplete penetrance. Age, gender, family history, polygenic risk, lifestyle, reproductive, hormonal, and environmental factors can affect the expressivity and penetrance of the disease.
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