Causal Explanations Research Articles

Self-satisfaction described by Zuckerman's alternative five factors of personality.

This study investigates the relationships between an individual's self-satisfaction within different life areas, which correspond to Bracken's self-concept primary domains (competence, family, social, physical, emotional, and academic domains), and Zuckerman's Alternative Five-Factor Model of Personality (AFFM). It is supposed that the AFFM, as a psychobiological personality model which allows causal explanations, could provide a comprehensive insight into the nature of satisfaction with self. The study included 489 adults (64% women), between 18 and 60 years old, who completed the short Self-Satisfaction Scale (SC-6) and the Zuckerman-Kuhlman-Aluja Personality Questionnaire (ZKA-PQ). Relations between personality factors and facets from the ZKA-PQ and self-satisfaction measures were analyzed using correlational and multiple regression analysis. The relationship of self-satisfaction with gender and age was also analyzed. Based on responses to scales, 11% to 43% of the variance in self-satisfaction responses was predicted by personality, age, and sex. Extraversion had positive predictive weights for each self-satisfaction dimension. Neuroticism had negative predictive weights which were significant except for satisfaction with family. Sensation seeking negatively predicted satisfaction with competencies, family, academic aspects, emotions, and overall satisfaction. Aggression had small negative predictor weights for satisfaction with social and academic aspects. Activity had significant positive predictor weights for competencies, academic aspects, emotions, and overall satisfaction. The findings suggest that personality predicts satisfaction with aspects of the self, and that the AFFM provides an adequate theoretical framework, which includes a lower level of personality traits in the explanation of the nature of a person's satisfaction, in general or related to specific life contexts.

'Almost nothing is firmly established': A History of Heredity and Genetics in Mental Health Science.

For more than a century, scientists have tried to find the key to causation of mental ill health in heredity and genetics. The difficulty of finding clear and actionable answers in our genes has not stopped them looking. This history offers important context to understanding mental health science today. This article explores the main themes in research on genetics and inheritance in psychiatry from the second half of the nineteenth century to the present day, to address the question: what is the history of genetics as a causative explanation in mental health science? We take a critical historical approach to the literature, interrogating primary and secondary material for the light it brings to the research question, while considering the social and historical context. We begin with the statistics gathered in asylums and used to 'prove' the importance of heredity in mental ill health. We then move through early twentieth century Mendelian models of mental inheritance, the eugenics movement, the influence of social psychiatry, new classifications and techniques of the postwar era, the Human Genome Project and Genome Wide Association Studies (GWAS) and epigenetics. Setting these themes in historical context shows that this research was often popular because of wider social, political and cultural issues, which impacted the views of scientists just as they did those of policymakers, journalists and the general public. We argue that attempting to unpick this complex history is essential to the modern ethics of mental health and genetics, as well as helping to focus our efforts to better understand causation in mental ill-health.For a succinct timeline of the history of psychiatric genetics, alongside the history of other proposed causes for mental ill-health, visit: https://historyofcauses.co.uk/.

Evaluation factors of e-justice intelligent services: An fsQCA analysis

E-justice intelligent services plays a significant role in promoting judicial efficiency and fairness. Based on previous studies, this research evaluates the quality of e-justice intelligent services from four factors, which are smart adjudication, class case recommendation, litigation risk assessment and big data analysis. We gain the data through expert interviews and analyze how these factors affect the quality of ejustice intelligent services using fsQCA. The results indicates that no single condition on its own leads to high quality of e-justice intelligent services. Smart adjudication, class case recommendation, big data analysis are core causal conditions, and litigation risk assessment is peripheral causal condition. Smart adjudication and class case recommendation have the most solutions. This study analyzes the evaluation factors of e-justice intelligent services, aiming at promoting the quality of e-justice intelligent services, so as to improve judicial efficiency.

Causal Histories of Psychological Factors and Cancer: From Psychosomatic Medicine to Neuroimmunomodulation.

Establishing causal relationships is essential in biology and medicine. However, various notions of causality have been operationalized at different times in various fields of the life and health sciences. While this is expected from a history or sociology of science point of view, as different accounts may correspond to what is valued in terms of establishing causal relationships at different times as well as in different fields of biology and medicine, this may come as a surprise for a present-day actor in those fields. If, over time, causal accounts have not been fully dismissed, then they are likely to invite some form of, potentially salutary, explanatory pluralism. In the decades following WWII, psychosomatic medicine could propose that psychological factors cause somatic diseases. But today, most medicine has to meet the standard of a randomized clinical trial before any causal relationship can be proposed. Instead, in biology, mechanisms seem to be the most-valued causal discourse to explain how phenomena of interest are brought about. Here, the focus will be on how psychoneuroimmunology, an interdisciplinary research field addressing interactions between the nervous system and immune system, and between behavior and health, has considered causal relationships between psychological factors and cancer. When it comes to causal explanations of links between psychological factors and cancer, psychoneuroimmunology is invited to consider the question of the directionality of these links as well as what and how factors causally contribute to cancer.

The Explanation One Needs for the Explanation One Gives. The Necessity of Explainable AI (XAI) for Causal Explanations of AI-related harm - Deconstructing the ‘Refuge of Ignorance’ in the EU’s AI liability Regulation

The Explanation One Needs for the Explanation One Gives. The Necessity of Explainable AI (XAI) for Causal Explanations of AI-related harm - Deconstructing the ‘Refuge of Ignorance’ in the EU’s AI liability Regulation

A Realist Evaluation of Social Care Practitioners' Experiences With and Understanding of Applied Healthcare Research.

Social care practitioners are often under-represented in research activity and output. Evidence-based practice enables social care practitioners to develop/engage the skills to evaluate evidence and be more actively involved in research. REalist Synthesis Of non-pharmacologicaL interVEntions for antipsychotic-induced weight gain (RESOLVE) is a NIHR-funded study where realist synthesis is used to understand and explain how, why, for whom, and in what contexts non-pharmacological interventions help service users, with severe mental illness, to manage antipsychotic-induced weight gain. Social care practitioners are a key part of the team providing care for people living with severe mental illness and therefore supporting antipsychotic-induced weight gain. The current study, RESOLVE 2, uses realist evaluation and RESOLVE as an illustrative example to help understand why and how social care practitioners engage (or not) with research. Semi-structured, audio-recorded interviews will be undertaken with a purposive sample of approximately 20 social care practitioners working with people who have severe mental illness, are treated with antipsychotics, and have experienced weight gain. Participants will be recruited from NHS Trusts and recruitment avenues such as social media and personal networks. Topics discussed during interviews will include barriers and facilitators to engagement in research, current, and past engagement as well as recommendations for researchers and other practitioners. Interview recordings will be transcribed verbatim and analyzed using realist evaluation which will allow in-depth causal explanations for research engagement. Better understanding of research engagement by social care practitioners will allow for evidence-based practice and better patient outcomes within these settings.

Persuading climate skeptics with facts: Effects of causal evidence vs. consensus messaging

Communicating the “97%’’ scientific consensus has been the centerpiece of the effort to persuade climate skeptics. Still, this strategy may not work well for those who mistrust climate scientists, to begin with. We examine how the American public—Republicans in particular—respond when provided with a relatively detailed causal explanation summarizing why scientists have concluded that human activities are responsible for climate change. Based on a preregistered survey experiment ( N = 3007), we assessed the effectiveness of detailed causal evidence versus traditional consensus messaging. We found that both treatments had noticeable effects on belief in human-caused climate change, with the causal evidence being slightly more effective, though we did not observe equivalent patterns for changes in attitudes toward climate policies. We conclude that conveying scientific information serves more as a remedy than a cure, reducing but not eliminating misperceptions about climate change and opposition to climate policies.

Emergence in Ontic Structural Realism

The paper outlines the understanding of emergence in Ontic Structural Realism of James Ladyman (and his co-author Ross). First, the notion of emergence is explored, surveying the various distinctions associated with it (ontological vs. epistemological, diachronic vs. synchronic, weak vs. strong). It turns out that Ross and Ladyman’s notion of emergence is that of weak epistemological emergence compatible with ontic reduction. Particular notions of emergence are associated with the objection embodied in the Generalized Causal Exclusion Argument. The latter is sketched and the solution of Ross and Ladyman is presented: first, in general, the notion of weak emergence is not threatened by this objection. Causal reduction associated with it ensures that there are no competing causal explanations, so no overdetermination arises. Second, there is a peculiar feature of Ross and Ladyman’s theory; namely, there is no causation on the fundamental level, only pattern dynamism. Causation emerges only on higher levels of special sciences. Hence, there is no problem of causal overdetermination.

Fenomenologia gestului între Heidegger și Flusser

In this article, I propose a phenomenological reflection on the problem of gesture. To begin with, I shed light on the difficulties encountered by the attempt to describe this phenomenon, given that the overflowing and irreducible plurality of gestures is constituted in various ways by the intertwining of several existential registers such as corporeality, intersubjectivity, affectivity and language. Then, I place the phenomenon of gesture in relation to bodily movement and the phenomenon of expressiveness, differentiating gestures from non-gestural movements and non-gestural expressions. Finally, I discuss two distinct phenomenological approaches which operate an enlargement of the concept of gesture, thus moving away from the primary meaning of the gesture as expressive, symbolic, intersubjectively anchored and affectively determined bodily movement. On the one hand, I show how Martin Heidegger rejects the relevance of the idea of expressivity to determine the gesture, emphasizing that all bodily movement, in order to be contrasted with the spatial movement of things, should be understood as gesture. On the other hand, I show how Vilém Flusser places the phenomenon of gesture in relation to the difference between moods and affect, understanding it as a symbolic movement for which we cannot find a satisfactory causal explanation.

The Competitive Securitization of Foreign Policy

The paper explores competitive securitizations of the Russian Federation vs. the European Union in the Georgian political public sphere through deconstruction of the pro-Western and pro-Russian public political narratives. The dis-information incursion and propaganda of the Russian Federation in the societal landscape of Georgia have become the primary tools of the Kremlin to undermine the soft-power policy the EU and the pro-Western agenda. The study reflects on the rotating political discourses on Russia vs. EU through narrative analysis and deconstructs those metanarratives, that securitize the pro-Western and pro-Russian foreign policy discourses and contribute to fragmentation of the political public sphere. The paper reflects on three interrelated clusters – politics, media and civil society – influenced by the pro-Russian strategic narratives tailored across ‘communities of grievances’ to counteract the Western liberal and normative-based agenda. Alternatively, the pro-Western narrative evolves around liberal conceptions, that tries to transform the post-Soviet Georgian society through ‘mental revolution.’ The political discourse analysis – understanding and interpreting meanings – refers to the public speeches of elites and policy documents for deconstruction of narrative structures, as their causal explanations provide insights into the ambiguous and contradictory representations of Russia and the West/EU in the securitized political public sphere in Georgia.

Using a boundary crossing lens to understand basic science educator and clinical educator collaboration in instructional design

Purpose Collaborations between basic science educators (BE) and clinical educators (CE) in medical education are common and necessary to create integrated learning materials. However, few studies describe experiences of or processes used by educators engaged in interdisciplinary teamwork. We use the lens of boundary crossing to explore processes described by BE and CE that support the co-creation of integrated learning materials, and the impact that this work has on them. Materials and methods We conducted qualitative content analysis on program evaluation data from 27 BE and CE who worked on 12 teams as part of a multi-institutional instructional design project. Results BE and CE productively engaged in collaboration using boundary crossing mechanisms. These included respecting diverse perspectives and expertise and finding efficient processes for completing shared work that allow BE and CE to build on each other’s contributions. BE and CE developed confidence in connecting clinical concepts with causal explanations, and willingness to engage in and support such collaborations at their own institutions. Conclusions BE and CE report the use of boundary crossing mechanisms that support collaboration in instructional design. Such practices could be harnessed in future collaborations between BE and CE.

Causal scientific explanations from machine learning

Causal scientific explanations from machine learning

Identification of causes and consequences of Kolberi among Iranian Kurdish women: a grounded theory study

BackgroundWomen turn to Kolberi for various reasons, which cause numerous challenges for them. Thus, it is imperative to identify these causes and problems. Since no study has ever been undertaken to deal with this participant, the present research aims to identify the causes and consequences of Kolberi among Kurdish women in Iran.MethodThe present research uses the grounded theory approach to investigate 28 female Kurdish Kolbers. To achieve several participants, purposive, snowball, and theoretical sampling methods were used, while face-to-face semi-structured interviews were used to gather data. The process of data collection and analysis took 10 months, from April to December 2022. The data were analyzed using the Strauss and Corbin method and MAXQDA-20018 software. The Guba and Lincoln criteria were also met to increase the trustworthiness of the results.FindingsAnalysis of the data led to 143 initial codes, 31 subcategories, and 9 main categories: Causal condition (individual characteristics and economic factors); predisposing conditions (social and cultural factors, familial factors); intervening conditions (advantages and characteristics of Kolberi); strategies (strengthening compatibility with Kolberi); and consequences (individual problems, social problems and positive consequences).ConclusionMeasures such as training occupational skills for women and providing employment conditions for them, increasing social, financial, and mental support for women without guardians, creating border markets, and expanding women's handicrafts can help prevent female Kolberi.

Causal Constraints in the Life and Social Sciences

Abstract This paper examines constraints and their role in scientific explanation. Common views in the philosophical literature suggest that constraints are non-causal and that they provide non-causal explanations. While much of this work focuses on examples from physics, this paper explores constraints from other fields, including neuroscience, physiology, and the social sciences. I argue that these cases involve constraints that are causal and that provide a unique type of causal explanation. This paper clarifies what it means for a factor to be a constraint, when such constraints are causal, and how they figure in scientific explanation.

Protocol for a realist evaluation of Recovery College dementia courses: understanding coproduction through ethnography

IntroductionSupport following a dementia diagnosis in the UK is variable. Attending a Recovery College course with and for people with dementia, their supporters and healthcare professionals (staff), may enable people...

An explainable deep reinforcement learning algorithm for the parameter configuration and adjustment in the consortium blockchain

In recent years, consortium blockchains have attracted considerable interest from the business communities and academia. To satisfy specific application requirements, appropriately configuring or adjusting the parameters is essential but challenging for developers when building the consortium blockchain. In this paper, the parameter configuration and adjustment for the consortium blockchain is transformed as a multi-objective optimization problem, and a novel explainable deep reinforcement learning (DRL) algorithm is proposed to solve the problem. On considering that existing DRL algorithms cannot be directly used in the consortium blockchain as they suffer from lacking of explainability, a causal model for configuring and adjusting the consortium blockchain’s parameters is proposed and integrated into the DRL algorithm. The causal model can be used to derive causal explanations of the DRL algorithm to increase its trustworthiness. Furthermore, the causal model-based DRL (C-DRL) algorithm can perform causal inference before taking action to eliminate unreasonable exploration and improve the DRL algorithm’s performance. The experimental results demonstrate the proposed algorithm provides the consortium blockchain with adaptive parameter configuration and adjustment to achieve sustainable high performance and security. Furthermore, the proposed algorithm increases the convergence speed of the vanilla algorithm by 49.3% and is more trustworthy than the vanilla DRL algorithm.

Critical Thinking, Formation, and Change.

In this paper, we propose an application of critical thinking (CT) to real-world problems, taking into account personal well-being (PB) and lifelong formation (FO). First, we raise a substantial problem with CT, which is that causal explanation is of little importance in solving everyday problems. If we care about everyday problems, we must treat the identification of causal relationships as a fundamental mechanism and action as a form of solution once the origin of the problem is unequivocally known. Decision-making and problem-solving skills should be the execution of the causal explanations reached. By acting this way, we change reality and achieve our goals, which are none other than those imposed by our PB. However, to achieve changes or results, we must have these fundamental competencies in CT, and these are not innate; we must acquire and develop them, that is, we must train ourselves to have CT competencies according to the demands of today's world. Finally, in this paper we propose a causal model that seeks to identify and test the causal relationships that exist between the different factors or variables that determine the CT-PB-FO relationship. We present some results on the relevance of causality and how to effectively form and address real-world problems from causality. However, there are still questions to be clarified that need to be investigated in future studies.

Moral explanation of moral judgements

Abstract“The wrongness of Albert's action causally explains why Jane judged that his action was wrong”. This type of causal moral explanation has been extensively discussed in the recent metaethical literature. This paper motivates the following claims about this type of moral explanation. First, a typical defence of this type of moral explanation suggested in the literature does not work because it predicts inaccurate modal information. Second, focusing on different aspects of the ways moral judgements are generated provides better chances for the defender of this type of moral explanation. Third, the strategy mentioned in the previous point leads us to the following alternative evaluative explanation: The property of being a harmful action explains a recognisable pattern of moral judgements observed in the relevant empirical studies. One crucial implication the paper alludes to is a localist approach to the debates concerning moral realism: We should consider each moral property's ontological genuineness separately, referring to specific empirical findings that are particularly relevant to the target moral property in question. Such a localist approach can provide solid resources for realists to respond to various anti‐realist challenges, such as an influential evolutionary debunking argument.

Fatalistic Beliefs, Naive Causal Explanations of Accidents and Road Safety Behaviors

Fatalistic Beliefs, Naive Causal Explanations of Accidents and Road Safety Behaviors

What are the causal conditions that lead to high or low environmental performance? A worldwide assessment

This study focuses on causal conditions that lead to high or low environmental performance (EPI) using fuzzy-set qualitative comparative analysis for 156 countries in 2018. Data for the EPI, economic growth, labor share of GDP, political freedom, the role of women, press freedom, corruption, and urbanization were used. Research findings allow us to conclude that no individual causal condition meets the necessary condition (thresholds) for high or low EPI. Five sufficient configurations for high EPI were found: (i) high GDP per capita is sufficient for high EPI; (ii) highly urbanized countries where corruption is absent; (iii) urbanized countries that protect individual rights and liberties and women's economic opportunities; (iv) high labor share of GDP coupled with the protection of individual freedom and women's economic rights; and (v) countries with high individual and press freedom where corruption is absent. Four sufficient configurations for low EPI were found: (vi) lack of protection of women's economic rights; (vii) lack of press freedom; (viii) low GDP per capita and high corruption rates, and urbanization as a peripheral condition; and (ix) low GDP per capita and high corruption rates and labor as a peripheral condition. Policymakers must acknowledge that there are many paths to improve environmental performance, contingent on the country's initial environmental development level.