Experimental entanglement of temporal order

The study of causal relations has recently been applied to the quantum realm, leading to the discovery that not all physical processes have a definite causal structure. While indefinite causal processes have previously been experimentally shown, these proofs relied on the quantum description of the experiments. Yet, the same experimental data could also be compatible with definite causal structures within different descriptions. Here, we present the first demonstration of indefinite temporal order outside of quantum formalism. We show that our experimental outcomes are incompatible with a class of generalised probabilistic theories satisfying the assumptions of locality and definite temporal order. To this end, we derive physical constraints (in the form of a Bell-like inequality) on experimental outcomes within such a class of theories. We then experimentally invalidate these theories by violating the inequality using entangled temporal order. This provides experimental evidence that there exist correlations in nature which are incompatible with the assumptions of locality and definite temporal order.

Feline sporotrichosis

Over the past two decades, many Brazilian cities have been reporting an increasing incidence and spread of feline sporotrichosis. The disease is neglected, and little is known about the causal processes underlying its epidemic occurrence. This study characterized the spatiotemporal dynamics of feline sporotrichosis in Guarulhos. Moreover, we proposed and tested a causal explanation for its occurrence and zoonotic transmission, giving a key role to social vulnerability. A direct acyclic graph represented the causal explanation, while Bayesian spatial models supported its test as well as the attribution of a risk-based priority index to the census tracts of the city. Between 2011 and 2017, the disease grew exponentially and the spatial spread increased. The model findings showed a dose-response pattern between an index of social vulnerability and the incidence of feline sporotrichosis. This pattern was not strictly monotonic, so some census tracts received a higher priority index than others with higher vulnerability. According to our causal explanation, there will not be effective prevention of feline and zoonotic sporotrichosis as long as social inequities continue imposing precarious livelihoods.

Long-Term Dataset of Tidal Residuals in New South Wales, Australia

Continuous water level records are required to detect long-term trends and analyse the climatological mechanisms responsible for extreme events. This paper compiles nine ocean water level records from gauges located along the New South Wales (NSW) coast of Australia. These gauges represent the longest and most complete records of hourly—and in five cases 15-min—water level data for this region. The datasets were adjusted to the vertical Australian Height Datum (AHD) and had the rainfall-related peaks removed from the records. The Unified Tidal Analysis and Prediction (Utide) model was subsequently used to predict tides for datasets with at least 25 years of records to obtain the associated tidal residuals. Finally, we provide a series of examples of how this dataset can be used to analyse trends in tidal anomalies as well as extreme events and their causal processes.

Unknotting reciprocal causation between organism and environment

In recent years, biologists and philosophers of science have argued that evolutionary theory should incorporate more seriously the idea of ‘reciprocal causation.’ This notion refers to feedback loops whereby organisms change their experiences of the environment or alter the physical properties of their surroundings. In these loops, in particular niche constructing activities are central, since they may alter selection pressures acting on organisms, and thus affect their evolutionary trajectories. This paper discusses long-standing problems that emerge when studying such reciprocal causal processes between organisms and environments. By comparing past approaches to reciprocal causation from the early twentieth century with contemporary ones in niche construction theory, we identify two central reoccurring problems: All of these approaches have not been able to provide a conceptual framework that allows (i) maintaining meaningful boundaries between organisms and environments, instead of merging the two, and (ii) integrating experiential and physical kinds of reciprocal causation. By building on case studies of niche construction research, we provide a model that is able to solve these two problems. It allows distinguishing between mutually interacting organisms and environments in complex scenarios, as well as integrating various forms of experiential and physical niche construction.

EPIDEMIOLOGY OF AUTOIMMUNE THYROID DISEASE

Most diseases involve many genes in complex interactions, in addition to physical and cultural environmental factors. If a disease is caused by genetic and environmental factors, its etiological origin can be referred to as having a multifactorial pattern. The common multifactorial diseases encompass environmental inuences on the causal processes. Thyroid is a multifactorial type of origin of disease. The epidemiological studies show that if thyroid disease is caused by the interaction of both genetic and environmental factors, then mostly it is autoimmune thyroid disease. When the antibodies attack the thyroid gland, it is called Auto Immune Thyroid Disease (AITD). The present study attempts to examine whether the occurrence of thyroid disease in a micro area is due to autoimmune conditions. To prove the fact clinically, blood of thyroid patients were collected and tested in a laboratory. The result shows that most of the patients have autoimmune thyroid disease. Moreover, some environmental and genetic factors were also examined since thyroid disease is a multifactorial origin of disease.

PATTERNS OF DEMOBILIZATION: A QUALITATIVE COMPARATIVE ANALYSIS (QCA) OF FAR-RIGHT DEMONSTRATION CAMPAIGNS

Scholarship on social movement lifecycles has focused on mobilization processes, with relatively less attention on the ends, demobilization. The intuitive connection between origins and ends has sometimes led to a conceptualization of demobilization as simply the failure to continue mobilizing, obscuring the distinct causal processes underlying demobilization. This article adds to recent studies foregrounding demobilization by studying the negative demobilization of large, far-right, demonstration campaigns. Using a subset from this population of cases—campaigns in Germany, England, and Austria between 1990 and 2015—the article applies qualitative comparative analysis (QCA) to this causally complex phenomenon. I find that demobilizing is conjunctural, with evidence of four patterns: closing opportunity, coercive state repression, civil countermobilization, and militant anti-far-right action. This article addresses an important—and conspicuously ubiquitous—population of cases, far-right demonstration campaigns and presents findings that reflect on critical issues in the study of far-right sociopolitics.

915Inference on Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLyses (ICE CRISTAL)

Focus of Presentation Causation is critical if epidemiology is to be relevant to public health. Mendelian Randomisation makes causal inference about from simply observing an association between the outcome and a genetic variable that has been conferred the title of “instrumental” because the proponents consider it satisfies some assumptions perfectly. We take this association as the starting point of a Popperian approach that tries to falsify causal hypotheses by relaxing assumptions and considering alternate models. Findings We developed methods to calculate test-of-fit statistics for different causal scenarios based on the joint changes in regression coefficients, using simulations and bootstrapping methods. Let Y be the outcome, X a putative cause, and G a potential instrumental variable associated with X and Y. We regress Y against X and G alone, and with X and G together. We predicted the changes to regression coefficients that should occur under three scenarios; (i) X causes Y, (ii) there is a factor C associated with Y, X and G. and (ii) Y causes X. We compared goodness-of-fit statistics across scenarios, and for combinations of scenarios (given multiple causal processes might co-exist). We present findings from application to data on body mass index and DNA methylation and compare with Mendelian Randomisation analyses. Conclusions/Implications Robust inference can be made but the sample sizes and strengths of associations need to be substantive. Key messages Causation is a fundamentally important issue that should, and can, be addressed by trying to disprove it, rather than by finding evidence for it.

Trends in U.S. Population Health: The Central Role of Policies, Politics, and Profits

Recent trends in U.S. health have been mixed, with improvements among some groups and geographic areas alongside declines among others. Medical sociologists have contributed to the understanding of those disparate trends, although important questions remain. In this article, we review trends since the 1980s in key indicators of U.S. health and weigh evidence from the last decade on their causes. To better understand contemporary trends in health, we propose that commonly used conceptual frameworks, such as social determinants of health, should be strengthened by prominently incorporating commercial, political-economic, and legal determinants. We illustrate how these structural determinants can provide new insights into health trends, using disparate health trajectories across U.S. states as an example. We conclude with suggestions for future research: focusing on structural causes of health trends and inequalities, expanding interdisciplinary perspectives, and integrating methods better equipped to handle the complexity of causal processes driving health trends and inequalities.

Pluralistic Attitude-Explanation and the Mechanisms of Intentional Action

According to the Causal Theory of Action (CTA), genuine actions are individuated by their causal history. Actions are bodily movements that are causally explained by citing the agent’s reasons. Reasons are then explained as some combination of propositional attitudes—beliefs, desires, and/or intentions. The CTA is thus committed to realism about the attitudes. This chapter explores current models of decision-making from the mind sciences, and argues that it is far from obvious how to locate the propositional attitudes in the causal processes they describe. The outcome of the analysis is a proposal for pluralism: there are several ways one could attempt to map states like ‘intention’ onto decision-making processes, but none will fulfill all of the roles attributed to the attitudes by the CTA.

A Systems View of Emotion in Socio-political Context

Most work to date in psychology and related sciences has examined simple, unidirectional causal processes of emotion affecting socio-political context or vice versa. In this classic, mechanistic view of science, each empirical observation stands on its own as a piece of some grander, not yet understandable, puzzle of nature. There have been repeated calls to eschew classic approaches in favor of systems meta-theory in psychology and related sciences. In this paper, we join these calls by arguing that systems meta-theory can better enable the study of emotions in socio-political contexts. We offer a brief primer on systems meta-theory, delineating three key beneficial features: multi-leveled, complex, and dynamic. Viewing emotion as a system of systems—within the person, their relationships (to others), and within the world (locally and globally)—enables fresh theory, method, and statistical analysis well suited to the study of emotion in a socio-political context.