Causal Importance Research Articles

Detecting dynamical causality via intervened reservoir computing

An abundance of complex dynamical phenomena exists in nature and human society, requiring sophisticated analytical tools to understand and explain. Causal analysis through observational time series data is essential in comprehending complex systems when controlled experiments are not feasible or ethical. Although data-based causal discovery methods have been widely used, there is still a lack of direct ways more aligned with the intuitive definition of causality, i.e., whether interventions on one element lead to changes in the subsequent development of others. To solve this problem, we propose the method of intervened reservoir computing (IRC) based on constructing a neural network replica of the original system and applying interventions to it. This approach enables controlled trials, thus observing the intervened evolution, in the digital twins of the underlying systems. Simulated and real-world data are used to test our approach and demonstrate its accuracy in inferring causal networks. Given the importance of causality in understanding complex dynamics, we anticipate that IRC could serve as a powerful tool for various disciplines to decipher the intrinsic mechanisms of natural systems from observational data.

Causal fairness assessment of treatment allocation with electronic health records

Objective:Healthcare continues to grapple with the persistent issue of treatment disparities, sparking concerns regarding the equitable allocation of treatments in clinical practice. While various fairness metrics have emerged to assess fairness in decision-making processes, a growing focus has been on causality-based fairness concepts due to their capacity to mitigate confounding effects and reason about bias. However, the application of causal fairness notions in evaluating the fairness of clinical decision-making with electronic health record (EHR) data remains an understudied domain. This study aims to address the methodological gap in assessing causal fairness of treatment allocation with electronic health records data. In addition, we investigate the impact of social determinants of health on the assessment of causal fairness of treatment allocation. Methods:We propose a causal fairness algorithm to assess fairness in clinical decision-making. Our algorithm accounts for the heterogeneity of patient populations and identifies potential unfairness in treatment allocation by conditioning on patients who have the same likelihood to benefit from the treatment. We apply this framework to a patient cohort with coronary artery disease derived from an EHR database to evaluate the fairness of treatment decisions. Results:Our analysis reveals notable disparities in coronary artery bypass grafting (CABG) allocation among different patient groups. Women were found to be 4.4%–7.7% less likely to receive CABG than men in two out of four treatment response strata. Similarly, Black or African American patients were 5.4%–8.7% less likely to receive CABG than others in three out of four response strata. These results were similar when social determinants of health (insurance and area deprivation index) were dropped from the algorithm. These findings highlight the presence of disparities in treatment allocation among similar patients, suggesting potential unfairness in the clinical decision-making process. Conclusion:This study introduces a novel approach for assessing the fairness of treatment allocation in healthcare. By incorporating responses to treatment into fairness framework, our method explores the potential of quantifying fairness from a causal perspective using EHR data. Our research advances the methodological development of fairness assessment in healthcare and highlight the importance of causality in determining treatment fairness.

Causal associations of Insomnia and postpartum depression: a two-sample mendelian randomization study.

Postpartum depression (PPD), a prevalent social-mental condition, impacts the mother and the newborn and several facets of their lives. It has been suggested that insomnia is related to both the occurrence and progression of PPD. However, because of lingering confounding and bias, it is impossible to determine the cause of this connection using observational analysis. In this study, we evaluate the causal importance of insomnia on postpartum depression using Mendelian randomization (MR). Utilizing summary data from genome-wide association studies (GWAS), a two-sample MR study was conducted. A GWAS dataset of IEU study of the United Kingdom Biobank phenotypes comprising 462,341 people of European heritage yielded 38 single-nucleotide polymorphisms (SNPs) for insomnia. The PPD data were provided by the FinnGen project and comprised 7604 cases and 59,601 controls. Inverse variance weighting (IVW) was utilized for the primary MR analysis, with weighted median and MR-Egger as sensitivity analyses. As a result, we found that genetically predicted insomnia was positively associated with postpartum depression. The odds ratios (OR) of PPD were 1.849 (95% (confidence interval) CI 1.011-3.381; p = 0.046). For the first time, the causative role of sleeplessness for postpartum depression has been extensively evaluated in the current two-sample MR investigation. Our findings show that insomnia and PPD are related causally.

A new causal centrality measure reveals the prominent role of subcortical structures in the causal architecture of the extended default mode network.

Network representation has been an incredibly useful concept for understanding the behavior of complex systems in social sciences, biology, neuroscience, and beyond. Network science is mathematically founded on graph theory, where nodal importance is gauged using measures of centrality. Notably, recent work suggests that the topological centrality of a node should not be over-interpreted as its dynamical or causal importance in the network. Hence, identifying the influential nodes in dynamic causal models (DCM) remains an open question. This paper introduces causal centrality for DCM, a dynamics-sensitive and causally-founded centrality measure based on the notion of intervention in graphical models. Operationally, this measure simplifies to an identifiable expression using Bayesian model reduction. As a proof of concept, the average DCM of the extended default mode network (eDMN) was computed in 74 healthy subjects. Next, causal centralities of different regions were computed for this causal graph, and compared against several graph-theoretical centralities. The results showed that the subcortical structures of the eDMN were more causally central than the cortical regions, even though the graph-theoretical centralities unanimously favored the latter. Importantly, model comparison revealed that only the pattern of causal centrality was causally relevant. These results are consistent with the crucial role of the subcortical structures in the neuromodulatory systems of the brain, and highlight their contribution to the organization of large-scale networks. Potential applications of causal centrality-to study causal models of other neurotypical and pathological functional networks-are discussed, and some future lines of research are outlined.

Causal evidence for the processing of bodily self in the anterior precuneus

To probe the causal importance of the human posteromedial cortex (PMC) in processing the sense of self, we studied a rare cohort of nine patients with electrodes implanted bilaterally in the precuneus, posterior cingulate, and retrosplenial regions with a combination of neuroimaging, intracranial recordings, and direct cortical stimulations. In all participants, the stimulation of specific sites within the anterior precuneus (aPCu) caused dissociative changes in physical and spatial domains. Using single-pulse electrical stimulations and neuroimaging, we present effective and resting-state connectivity of aPCu hot zone with the rest of the brain and show that they are located outside the boundaries of the default mode network (DMN) but connected reciprocally with it. We propose that the function of this subregion of the PMC is integral to a range of cognitive processes that require the self's physical point of reference, given its location within a spatial environment.

Developing the genotype-to-phenotype relationship in evolutionary theory: A primer of developmental features.

For decades, there have been repeated calls for more integration across evolutionary and developmental biology. However, critiques in the literature and recent funding initiatives suggest this integration remains incomplete. We suggest one way forward is to consider how we elaborate the most basic concept of development, the relationship between genotype and phenotype, in traditional models of evolutionary processes. For some questions, when more complex features of development are accounted for, predictions of evolutionary processes shift. We present a primer on concepts of development to clarify confusion in the literature and fuel new questions and approaches. The basic features of development involve expanding a base model of genotype-to-phenotype to include the genome, space, and time. A layer of complexity is added by incorporating developmental systems, including signal-response systems and networks of interactions. The developmental emergence of function, which captures developmental feedbacks and phenotypic performance, offers further model elaborations that explicitly link fitness with developmental systems. Finally, developmental features such as plasticity and developmental niche construction conceptualize the link between a developing phenotype and the external environment, allowing for a fuller inclusion of ecology in evolutionary models. Incorporating aspects of developmental complexity into evolutionary models also accommodates a more pluralistic focus on the causal importance of developmental systems, individual organisms, or agents in generating evolutionary patterns. Thus, by laying out existing concepts of development, and considering how they are used across different fields, we can gain clarity in existing debates around the extended evolutionary synthesis and pursue new directions in evolutionary developmental biology. Finally, we consider how nesting developmental features in traditional models of evolution can highlight areas of evolutionary biology that need more theoretical attention.

“THE GOD WITH CLAY”: THE IDEA OF DEEP INCARNATION AND THE INFORMATIONAL UNIVERSE

AbstractThis article explores the relations between the idea of deep incarnation and scientific ideas of an informational universe, in which mass, energy, and information belong together. It is argued that the cosmic Christologies developed in the vein of Cappadocian theology (fourth century) and the Franciscan theologian Bonaventure (thirteenth century) can be interpreted as precursors of an informational worldview by consistently blending “formative” and “material” aspects of creativity. Reversely, contemporary sciences of information can enlarge the scope of the contemporary view of deep incarnation. I propose three hypotheses for showing how and why. First, mass, energy, and information have an equal causal importance for explaining reality. Second, just as transformation presupposes communication, so communication presupposes information. Third, contemporary science can elucidate seminal concerns of the idea of deep incarnation, insofar as informational structures pave the way for information capture, communication, and transformation. At the level of organismic life, new features of embodied cognition and emotion come up, important for understanding the organismic depth of the concrete incarnation in Jesus of Nazareth.

Mendelian randomisation study of body composition and depression in people of East Asian ancestry highlights potential setting-specific causality

BackgroundExtensive evidence links higher body mass index (BMI) to higher odds of depression in people of European ancestry. However, our understanding of the relationship across different settings and ancestries is limited. Here, we test the relationship between body composition and depression in people of East Asian ancestry.MethodsMultiple Mendelian randomisation (MR) methods were used to test the relationship between (a) BMI and (b) waist-hip ratio (WHR) with depression. Firstly, we performed two-sample MR using genetic summary statistics from a recent genome-wide association study (GWAS) of depression (with 15,771 cases and 178,777 controls) in people of East Asian ancestry. We selected 838 single nucleotide polymorphisms (SNPs) correlated with BMI and 263 SNPs correlated with WHR as genetic instrumental variables to estimate the causal effect of BMI and WHR on depression using the inverse-variance weighted (IVW) method. We repeated these analyses stratifying by home location status: China versus UK or USA. Secondly, we performed one-sample MR in the China Kadoorie Biobank (CKB) in 100,377 participants. This allowed us to test the relationship separately in (a) males and females and (b) urban and rural dwellers. We also examined (c) the linearity of the BMI-depression relationship.ResultsBoth MR analyses provided evidence that higher BMI was associated with lower odds of depression. For example, a genetically-instrumented 1-SD higher BMI in the CKB was associated with lower odds of depressive symptoms [OR: 0.77, 95% CI: 0.63, 0.95]. There was evidence of differences according to place of residence. Using the IVW method, higher BMI was associated with lower odds of depression in people of East Asian ancestry living in China but there was no evidence for an association in people of East Asian ancestry living in the USA or UK. Furthermore, higher genetic BMI was associated with differential effects in urban and rural dwellers within China.ConclusionsThis study provides the first MR evidence for an inverse relationship between BMI and depression in people of East Asian ancestry. This contrasts with previous findings in European populations and therefore the public health response to obesity and depression is likely to need to differ based on sociocultural factors for example, ancestry and place of residence. This highlights the importance of setting-specific causality when using genetic causal inference approaches and data from diverse populations to test hypotheses. This is especially important when the relationship tested is not purely biological and may involve sociocultural factors.

Are There Really Social Causes?

This article investigates the causal efficacy of social properties, which faces the following puzzle. First, for both intuitive and scientific reasons, it seems social properties have causal import. But, second, social properties are also characteristically extrinsic: to have some social property depends, in typical cases, on what one’s society is like around them. And, third, there is good reason to doubt that extrinsic properties make a genuine causal contribution. After elaborating on these three claims, I defend the following resolution to the puzzle: social causation occurs at the level at which social properties are intrinsic.

Green Finance and Sustainable Development: Exploring Dynamic Causal Links and Global Implications

This research investigates the potential causal relationship among sustainable development and green finance on a world level, using data from 2011 to 2023. In this study, the researcher utilized the bootstrap rolling-window Granger causal relationship test to investigate the contributions of different stakeholders to sustainable development by participating in green finance initiatives. The results of the analysis demonstrate that green finance has a positive impact on sustainable development across different time periods. While green finance represents a crucial financing mechanism for advancing sustainable development goals, its direct influence on SD remains unproven. Additionally, this analysis identifies distinct causal relationships in different sub periods, emphasizing the importance of context-specific causality. Moreover, in specific contexts, the direction of causality holds significant implications. Therefore, we propose that governments and international organizations play a pivotal role in guiding high-quality green investments and implementing risk mitigation strategies within the established system framework. Furthermore, enhancing the standards for categorizing green finance, developing comprehensive evaluation systems, and promoting transparent information disclosure related to GF can foster greater contributions by countries to sustainable development initiatives.

Empirical adaptationism revisited: is it testable and is it worth testing?

Empirical adaptationism is often said to be an empirical claim about nature, which concerns the overall relative causal importance of natural selection in evolution compared with other evolutionary factors. Philosophers and biologists who have tried to clarify the meaning of empirical adaptationism usually share, explicitly or implicitly, two assumptions: (1) Empirical adaptationism is an empirical claim that is scientifically testable; (2) testing empirical adaptationism is scientifically valuable. In this article, I challenge these two assumptions and argue that both are unwarranted given how empirical adaptationism is currently formulated. I identify a series of conceptual and methodological difficulties that makes testing empirical adaptationism in a biologically non-arbitrary way virtually impossible. Moreover, I show that those in favor of testing empirical adaptationism have yet to demonstrate the distinctive value and necessity of conducing such a test. My analysis of the case of empirical adaptationism also provides reasons for scientists to reconsider the value and necessity of engaging in scientific debates involving the notion of overall relative causal importance.

Learn German, Buy German? Language‐learning opportunities abroad and exports

Using data on the presence of the Goethe Institutes (GI) in 134 importer countries between 1978 and 2014, we study the effect that language learning opportunities abroad have on German exports. We employ a gravity model of trade with a single exporter and use the Poisson Pseudo-Maximum Likelihood (PPML) estimator to measure the relationship of interest. To gauge the importance of potential reverse causality, we also estimate the effect that institutes have on Swiss exports. Our findings for both Germany and German-speaking Swiss cantons show that institutes do stimulate exports to GI-hosting countries but that this effect is confined to institutes offering language training services. This finding suggests that language requirements and acquisition underlie the positive link found between institutes and exports. This reading of our findings receives further support in additional explorations, where we study exports differentiated by Rauch (1999, Journal of International Economics, 48(1), 7) product categories to account for differing communication requirements in trading.

Statistical Control Requires Causal Justification

It is common practice in correlational or quasiexperimental studies to use statistical control to remove confounding effects from a regression coefficient. Controlling for relevant confounders can debias the estimated causal effect of a predictor on an outcome; that is, it can bring the estimated regression coefficient closer to the value of the true causal effect. But statistical control works only under ideal circumstances. When the selected control variables are inappropriate, controlling can result in estimates that are more biased than uncontrolled estimates. Despite the ubiquity of statistical control in published regression analyses and the consequences of controlling for inappropriate third variables, the selection of control variables is rarely explicitly justified in print. We argue that to carefully select appropriate control variables, researchers must propose and defend a causal structure that includes the outcome, predictors, and plausible confounders. We underscore the importance of causality when selecting control variables by demonstrating how regression coefficients are affected by controlling for appropriate and inappropriate variables. Finally, we provide practical recommendations for applied researchers who wish to use statistical control.

Application of DEMATEL and ANP in Fruit Bag in Service Design

Causal relationship and importance of evaluation factors for purchasing decisions were investigated by taking the kiwifruit bag design as the research object and by using the decision-making laboratory analysis method (DEMATEL). It was found that the three most important evaluation factors before purchasing kiwifruit bags are "beauty" as the influencing factor, "operability" and "durability" as the main factors. Purchasing decisions of Kiwifruit bags are influenced by the three factors. Therefore, it is recommended to use the DEMATEL method to investigate possible factors for marketing products. The modeling process quantitatively evaluates simple interacting factors compared to complex factors, and the result is used to determine future directions of product designs.

Causalidad y regulación: algunas dificultades de los ensayos controlados aleatorizados

The article focuses on the key importance of causality in regulatory activities in the social sciences and especially in nutrition. After a brief presentation (Sec. 1), the text proposes several ways of examining the notion of cause and of conceiving it from a philosophical perspective (Sec. 2). Section 3 particularly discusses the counterfactual way, understood as a broad approach to conceiving causation in terms of its relationship to randomized controlled trials (RCT) and, by derivation, to the objective character of the latter. Section 4 examines the evidence underlying RCTs and the role they play in regulation. Evidences are linked to causal statements that are usual in RCTs and whose nature is not exempt from a criticism in areas such as the evidence-based medicine (EBM) (Sec. 5) and, above all, nutritional sciences (Sec. 6). In Section 7, it is claimed a plural methodological perspective that would improve the production of results in nutrition that would act as a basis for making regulatory decisions. The last section closes the argument of the article.

Does aggression lead to hate? Detecting and reasoning offensive traits in hinglish code-mixed texts

Aggression is a prominent trait of human beings that can affect social harmony in a negative way. The hate mongers misuse the freedom of speech in social media platforms to flood with their venomous comments in many forms. Identifying different traits of online offense is thus inevitable and the need of the hour. Existing studies usually handle one or two offense traits at a time, mainly due to the lack of a combined annotated dataset and a scientific study that provides insights into the relationship among the traits. In this paper, we study the relationship among five offense traits – aggression, hate, sarcasm, humor, and stance in Hinglish (Hindi-English) social media code-mixed texts. We employ various state-of-the-art deep learning systems at different morphological granularities for the classification across five offense traits. Our evaluation of the unified framework suggests ∼90% performance across all major traits. Furthermore, we propose a novel notion of causal importance score to quantify the effect of different abusive keywords and the overall context on the offensiveness of the texts.

Household Waste Separation Intentions in Mongolia: Persuasive Communication Leads to Perceived Convenience and Behavioral Control

This study contributes by developing a set of household waste separation (HWS) attributes to address waste mishandling and to enhance waste separation intentions in households. In Mongolia, a lack of waste separation at the household level needs to be addressed to improve municipal solid waste management systems. However, prior studies have not established attributes in a hierarchical structure, nor do they understand their cause-effect interrelationships. First, the fuzzy Delphi method (FDM) was used to screen out the unnecessary attributes in qualitative information. The fuzzy decision-making trial and evaluation laboratory (FDEMATEL) was then applied to understand the hierarchical structure of the attributes and their cause-effect interrelationships. The study identifies a valid set of attributes consisting of five aspects and 17 criteria under uncertainties. A hierarchical framework consisting of environmental attitudes, social norms, perceived behavioral control, perceived convenience, and persuasive communication is provided. The findings reveal that persuasive communication and environmental attitudes are causal group aspects. Furthermore, persuasive communication has a strong causal impact and higher importance in improving HWS intentions, and it leads to perceived convenience and behavioral control. For policymakers, credibility of information, knowledge and information, awareness of consequences, willingness to sort, and perceived policy effectiveness are the key causal criteria for enhancing HWS intentions. Theoretical and practical policy implications are discussed.

From Spectatorship to “Survivorship” in Five Critical Propositions

Often theorized through the negative framework of addiction or passivity, binge-watching has been transformed into a civic duty and a mode of survival during the COVID-19 pandemic. Exploring this recent plot-twist in bingeing scholarship, this article proposes five new ways to study the most dominant spectatorial mode under corona-capitalism. These propositions include studying how the pandemic turned bingeing into an antidote to “languishing,” a feeling of sadness and exhortation that, if unrecognized, might lead to depression; exploring co-watching apps in order to move away from the cliché of bingeing as an individual activity; unpacking the importance of narrative causality during the pandemic’s prolonged structure and temporal limbo; paying close attention to interface design decisions, such as the addition of a “playback speed” feature to Netflix in August 2020; and, finally, demonstrating how binge-watching trains viewers to ignore their basic biological needs while turning them into unpaid laborers.

Altered sense of self during seizures in the posteromedial cortex

The posteromedial cortex (PMC) is known to be a core node of the default mode network. Given its anatomical location and blood supply pattern, the effects of targeted disruption of this part of the brain are largely unknown. Here, we report a rare case of a patient (S19_137) with confirmed seizures originating within the PMC. Intracranial recordings confirmed the onset of seizures in the right dorsal posterior cingulate cortex, adjacent to the marginal sulcus, likely corresponding to Brodmann area 31. Upon the onset of seizures, the patient reported a reproducible sense of self-dissociation-a condition he described as a distorted awareness of the position of his body in space and feeling as if he had temporarily become an outside observer to his own thoughts, his "me" having become a separate entity that was listening to different parts of his brain speak to each other. Importantly, 50-Hz electrical stimulation of the seizure zone and a homotopical region within the contralateral PMC induced a subjectively similar state, reproducibly. We supplement our clinical findings with the definition of the patient's network anatomy at sites of interest using cortico-cortical-evoked potentials, experimental and resting-state electrophysiological connectivity, and individual-level functional imaging. This rare case of patient S19_137 highlights the potential causal importance of the PMC for integrating self-referential information and provides clues for future mechanistic studies of self-dissociation in neuropsychiatric populations.

Measuring the effect of cash credit on industrial production in Iraq for the period of 2003-2020

The monetary sector in Iraq occupies a distinguished position as it manages the movement of money, which is the main engine of economic activity. The importance of research is determined by studying the relationship between cash credit and its role in fostering economic activities, especially in the industrial sector. The authors of the research aim to study and analyze the nature of domestic credit in Iraq and its role in developing the industrial sector. The research originates from the hypothesis that credit changes in Iraq have a major role in developing industrial economic activities. In order to reach the purpose of the research and verify the hypothesis, an analysis of the domestic crediting in Iraq, along with its role in the development of the industrial sector, and the causal importance of the types of cash credit in Iraq was carried out. In this study, the descriptive inductive approach is relied on the analysis of monetary credit indicators in Iraq. In addition to the quantitative method of analyzing the available data on the relationship between cash credit and the industrial sector, the authors used the EViews 12 software.