Causal Theory Research Articles

Supposed Corpses and Correspondence

The correspondence requirement is a fundamental doctrinal principle in Anglo-American criminal law. It maintains that, in general, a particular relation between mens rea and actus reus is necessary for liability. Yet the nature of this relation is contested. Contemporaneity Theorists maintain that correspondence requires temporal overlap between mens rea and actus reus, while Causal Theorists maintain that correspondence is a non-deviant causal connection. In this paper, I argue that neither Contemporaneity Theory nor Causal Theory is able to account for the intuition that a special class of defendants—defendants in so-called supposed corpse cases—are liable for murder. Supposed corpse defendandts attempt to kill at t1, erroneously suppose they have done so, and then act again to cause death at t2. I go on to provide a novel positive proposal of correspondence in such cases. I argue that supposed corpse defendants are liable for murder because their killing is explained by ignorance that is in turn explained by an apparently successful execution of their intention to kill. The result serves as demonstration that the relation between intention and action grounding culpability is not the same as the relation grounding an action's status as intentional.

Understanding bus network delay propagation: Integration of causal inference and complex network theory

Understanding bus network delay propagation: Integration of causal inference and complex network theory

Minimal operational theories: classical theories with quantum features

Abstract We introduce a class of probabilistic theories, termed Minimal Strongly Causal Operational Probabilistic Theories, where system dynamics are constrained to the minimal set of operations consistent with the set of states and permitting conditional tests. Specifically, the allowed instruments are limited to those derived from compositions of preparations, measurements, swap transformations, and conditional operations. We demonstrate that minimal theories with conditioning and a spanning set of non-separable states satisfy two quantum no-go theorems: no-information without disturbance and no-broadcasting. As a key example, we construct Minimal Strongly Causal Bilocal Classical Theory, a classical toy-theory that lacks incompatible measurements, preparation uncertainty relations, and is noncontextual (both Kochen–Specker and generalised), yet exhibits irreversibility of measurement disturbance, no-information without disturbance, and no-broadcasting. Therefore, the latter three properties cannot be understood per se as signatures of non-classicality. We further explore distinctions between a theory and its minimal strongly causal counterpart, showing that while the minimal strongly causal version of quantum theory diverges from full quantum theory, the same does not hold for classical theory. Additionally, we establish the pairwise independence of the properties of simpliciality, strong causality, and local discriminability.

Fluctuations and Correlations in Causal Set Theory

Abstract We study the statistical fluctuations (such as the variance) of causal set quantities, with particular focus on the causal set action. To facilitate calculating such fluctuations, we develop tools to account for correlations between causal intervals with different cardinalities. We present a convenient decomposition of the fluctuations of the causal set action into contributions that depend on different kinds of correlations. This decomposition can be used in causal sets approximated by any spacetime manifold M. Our work paves the way for investigating a number of interesting discreteness effects, such as certain aspects of the Everpresent Λ cosmological model.

College students’ entrepreneurship education path and management strategy of start-up enterprises using causal attribution theory

The current social entrepreneurship situation is not ideal. This study aims to enhance the effectiveness of college students’ entrepreneurship education and improve the safety factor of start-up enterprises. Firstly, the current situation of college students’ entrepreneurship education is studied through questionnaires and literature review. Secondly, the risk-influencing factors of start-up enterprises are collected and analyzed through deep learning (DL) and artificial intelligence (AI) technologies. Finally, drawing on the causal attribution theory, the influencing factors and entrepreneurial risks of college students’ entrepreneurship are analyzed. The reasonable path of college students’ entrepreneurship education and the management strategy of start-up enterprises are proposed. The results indicate that employing DL and AI in college students’ entrepreneurship education facilitates identifying influencing factors, allowing for timely adjustments and the development of effective educational paths tailored to students’ needs. Moreover, the management strategy based on DL and AI can help start-up enterprises accurately and timely predict risks, find their source of risks, and minimize potential losses. The study also identifies several key factors affecting the management strategy of start-up enterprises. The most influential is the wrong decision-making of managers, with a coefficient of 9, followed by employee turnover, with a coefficient of 8. The corresponding influence weights of these two factors are the highest, with values of 0.175 and 0.138, respectively. In contrast, internal employee resistance has the lowest influence weight, at 0.024. This study provides valuable theoretical support for the future development of entrepreneurship education for college students and contributes to refining the management strategies of start-up enterprises.

The effectiveness of harvest for limiting wildlife disease: Insights from 20 years of chronic wasting disease in Wyoming.

Effective, practical options for managing disease in wildlife populations are limited, especially after diseases become established. Removal strategies (e.g., hunting or culling) are used to control wildlife diseases across a wide range of systems, despite conflicting evidence of their effectiveness. This is especially true for chronic wasting disease (CWD), an untreatable, fatal prion disease threatening cervid populations across multiple countries, for which recreational harvest has been suggested as an important disease control strategy. Using observational data to evaluate whether harvest effectively limits CWD prevalence has been difficult because statistical relationships between harvest and disease prevalence can arise from a causal effect of harvest (i.e., harvest's impacts on prevalence via changes in transmission or demographic structure) or from a number of alternative mechanisms. For instance, correlations between harvest and disease prevalence can also be driven by disease's impacts on population size and harvest (i.e., reverse causality) or from confounding variables (e.g., habitat or geographic location) that impact both harvest rates and disease prevalence. We analyzed two decades of surveillance data (2000-2021) from 10 mule deer herds in Wyoming, using statistical approaches informed by causal inference theory, to test for the effects of harvest on CWD prevalence. Herds with consistently high harvest pressure across 20 years had significantly lower prevalence. Our models predicted that harvesting 40% of adult males per year across 20 years would maintain prevalence below 5% on average, whereas if only 20% of males were harvested in each year, prevalence would increase to >30% by year 20. Moreover, shifting the relative harvest pressure within a herd over a shorter period (3 years) reduced subsequent prevalence, albeit to a smaller degree. Although high harvest is unlikely to completely eradicate CWD, our analysis suggests that maintaining hunting pressure on adult males is an important tactic for slowing CWD epidemics within mule deer herds. Our study also provides guidance for future analyses of longitudinal surveillance data, including the importance of demographic data and appropriate time lags.

Wildlife policy, the food system and One Health: a complex systems analysis of unintended consequences for the prevention of emerging zoonoses in China, the Democratic Republic of the Congo and the Philippines

IntroductionEvolving human–wildlife interactions have contributed to emerging zoonoses outbreaks, and pandemic prevention policy for wildlife management and conservation requires enhanced consideration from this perspective. However, the risk of unintended consequences...

Case study of disseminated leiomyomatosis with urological and colorectal involvement and a literature review

Disseminated peritoneal leiomyomatosis (DPL), also known as diffuse peritoneal leiomyomatosis, is a rare disease characterized by a sub peritoneal proliferation of benign nodules, mainly composed of benign smooth muscle cells, macroscopically mimicking peritoneal carcinosis. We report the case of a 60-year-old patient, with hypertension under treatment, being followed for the management of pauci-symptomatic abdominopelvic masses, evolving in a context of conservation of the general state, who underwent hysterectomy with adnexectomy by laparotomy for uterine myoma. Imaging revealed three masses, extending from the perigastric to the pelvic region, with areas of necrosis, moderate peritoneal effusion and lumbo-aortic and primitive iliac lymph nodes with small infracentimetric axes. The management consisted of a complete cytoreduction. Postoperative management was straightforward. LPD is a rare condition, with around 200 cases published in the literature. Its incidence is estimated at around 1/10,000,000, given the generally asymptomatic nature of the disease. The etiopathogenesis of this condition remains poorly elucidated, although several causal theories have been described in the literature, including hormonal, iatrogenic and congenital or hereditary. The management of LPD is not currently standardized, but surgery remains the gold standard. LPD is a rare, benign condition characterized by sub peritoneal proliferation of smooth muscle cells. It occurs most frequently in women of childbearing age, but can also occur in postmenopausal women and men. Treatments for LPD are not standardized, and further studies are required in the near future.

Challenging The Form of Responsibility in Drug Policies That Adversely Affect Consumers: Causality Theory As An Analytical Lens

It becomes a real polemic when a drug intended for health development to support national development actually becomes a serious threat to health itself. The purpose of this study is to answer the issue of responsibility for drugs that cause adverse effects on consumers. This research uses normative juridical method. In this research, it is found that the constitution has massively regulated the relationship that implies responsibility in terms of drugs that cause adverse effects to consumers. Based on the theory of causality, in addition to pharmaceutical companies that can be charged with absolute liability in accordance with the provisions of Article 19 of the Consumer Protection Law, the Food and Drug Supervisory Agency (BPOM) can also be blamed, especially if the elements of abuse of duty and negligence are met based on Presidential Regulation No. 80 of 2017 concerning BPOM.

Reconsidering mechanisms in social science research: the varied uses of an explanatory metaphor

AbstractThis article reconsiders the role of mechanisms in social science research. The study of mechanisms has been recognized as a fundamental task for a methodologically diverse range of social scientific approaches. This raises questions of what roles mechanisms play for causal explanations and if there are uses that are more reasonable than others. To address these questions the article, first, discusses competing arguments for the causal theory underpinning mechanisms. On the basis of these discussions the paper emphasizes the heuristic role of mechanisms as an explanatory devise, serving a crucial role for causal explanations. Secondly, it endeavors to explore the diverse ways mechanisms are employed, especially in contemporary political science research, to highlight limits and benefits with different approaches. The discussion helps reconsider existing fault lines in debates over mechanisms, including the relationship between qualitative and quantitative techniques in empirical research centered on mechanistic explanations.

Definition and identification of causal ratio effects.

In generalized linear models, the effect of a treatment or intervention is often expressed as a ratio (e.g., risk ratio and odds ratio). There is discussion about when ratio effect measures can be interpreted in a causal way. For example, ratio effect measures suffer from noncollapsibility, that is, even in randomized experiments, the average over individual ratio effects is not identical to the (unconditional) ratio effect based on group means. Even more, different ratio effect measures (e.g., simple ratio and odds ratio) can point into different directions regarding the effectiveness of the treatment making it difficult to decide which one is the causal effect of interest. While causality theories do in principle allow for ratio effects, the literature lacks a comprehensive derivation and definition of ratio effect measures and their possible identification from a causal perspective (including, but not restricted to randomized experiments). In this article, we show how both simple ratios and odds ratios can be defined based on the stochastic theory of causal effects. Then, we examine if and how expectations of these effect measures can be identified under four causality conditions. Finally, we discuss an alternative computation of ratio effects as ratios of causally unbiased expectations instead of expectations of individual ratios, which is identifiable under all causality conditions and consistent with difference effects. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Error Theories of Absence Causation Are Not (Yet) Adequately Motivated

Error Theories of Absence Causation Are Not (Yet) Adequately Motivated

Effect of resolution on simulated teleconnections to winter North Atlantic circulation inferred from a causal network derived from expert elicitation

When designing a set of climate projections for a given amount of supercomputing, the choice of resolution affects the ensemble size that can be afforded. The larger sample size helps to quantify uncertainties more robustly and provide better statistics to understand the projections. The trade-off is that the use of coarser resolution risks some compromise on quality in representing processes that could play a crucial role in the climate response. But what exactly is the added value of the enhanced resolution? We use two tools, which are applicable to a broader set of applications, to assess this for processes (teleconnections) that drive the year-to-year variability of late winter circulation over the North Atlantic. First, a causal network, which captures the teleconnections that relate key drivers of variability to late winter North Atlantic Oscillation (NAO), is elicited from experts in seasonal forecasting. Causal Inference theory is then used to estimate the teleconnection strengths. Second, we use two parallel perturbed parameter ensembles (PPEs) of coupled control simulations based on HadGEM3-GC3 at low and medium atmosphere/ocean resolutions. Combining the two tools allows us to identify teleconnections which have strengths (a) controlled by parameters, and (b) that are altered in a systematic way across parameter space by the enhanced resolution. Overall, the medium resolution is marginally better than the lower resolution, notably in the way El Niño-Southern Oscillation (ENSO) affects the Indian Ocean Dipole. For many of the teleconnections, most model configurations have weaker relationships than observed. Several teleconnections are shown to have modest parametric effects that produce correlated changes across the two PPEs. However, the ensemble size would need to be increased to better identify the key parameters and processes.

Risk factors contributing to interproximal contact loss between an implant crown and a natural tooth.

Interproximal contact loss (ICL) is considered a prevalent complication for a tooth abutting an implant restoration. While numerous potential causes for ICL have been presented, there is no consensus. A review of the current literature with a focus on possible risk factors was performed. A PubMed search using keywords "implant OR dental implants OR implant supported prosthesis AND proximal contact loss OR ICL OR loss of interproximal contact OR open contact OR interproximal open contact OR adjacent natural teeth" resulted in 81 citations, 9 of which were relevant to the focus question. Additional references were culled from the reference lists in the identified articles. Systematic reviews, case series, and case reports were reviewed with a focus on causation, association, or correlation. Eight systematic reviews and 14 case series were reviewed. The prevalence of ICL has been reported to be as low as 16% and as high as 66%. ICL was more common on the mesial side of implants and when a tooth abuts a splinted implant restoration. The absence of a uniform definition to accurately describe an interproximal (IP) contact and an open IP contact is demonstrated in the literature. A lack of standardized measurement strategies that relate to a needed consensus definition further exacerbates the broad range of reported results regarding ICL. The lack of controls for almost all the ICL literature makes it difficult to draw conclusions and comparisons to unrestored, natural tooth IP contacts and the prevalence of ICL in this patient population. As a result, the available studies are inadequate to support a causal theory and the potential risk factors associated with ICL. There is a large range of reported prevalence for IP contact loss. ICL is more common when a natural tooth abutsa splinted implant restoration. ICL is more common on the mesial, as opposed to the distal, of an implant retained restoration. Consensus in the definition and measurement strategies for ICL needs to be established to provide standardized terminology and methodology. Potential risk factors such as occlusion, restorative material, and tooth contact area need to be investigated.

Counterintuitive Scenarios in Discrete Gravity Without Quantum Effects or Causality Violations

In certain established approaches to quantum gravity, such as causal set theory and causal dynamical triangulations, discrete spacetime structure is taken to be a primary feature, not a secondary effect of “quantizing” a pre-existing classical continuum-based theory, as is done in approaches such as string theory and loop quantum gravity. For a priori discrete models, the full quantum theory is often obtained via some version of Feynman’s sum-over-histories approach, in which each “history” is a discrete object viewed as a classical spacetime. Counterintuitive physical scenarios such as Schrödinger’s cat or the grandfather paradox are typically associated with either quantum effects or causality violations, but we demonstrate that equally bizarre scenarios can arise at a purely classical level in the discrete causal context due to symmetry considerations. In particular, the graph-theoretic phenomenon of pseudosimilarity leads to situations in which alternative events occurring at physically distinguishable locations in the universe can cause different parts of the universe to “swap identities” in a fugue-like manner alien to continuum-based theories. This phenomenon is perhaps best understood as an extension of the relativity principle, which we call relativity of identity.

On the Origin of Entrepreneurial Theories: How Entrepreneurs Craft Complex Causal Models with Theorizing and Data

The emerging theory-based view depicts entrepreneurs as sophisticated thinkers who form, update, and act on rich causal theories. In support of this view, recent empirical work has demonstrated both (a) the value of theories as well as (b) the importance of experimentation for testing and refining theories. Yet, the process by which entrepreneurs initially form these theories remains largely unobserved. To address this gap, we conduct a longitudinal study of nine consumer platform ventures over five years. Our primary contribution is to illuminate how entrepreneurs move from the spark of an initial idea to an actionable theory. This process begins with a thesis, which is an initial, poorly formed idea that guides subsequent learning and theorizing. To elaborate this thesis, entrepreneurs then knit together multiple distinct mental theorizing practices, as well as different approaches to generating new data. Extending prior work, we articulate the distinct roles these practices play in terms of adding novelty, identifying new subproblems, and explicating beliefs. We also add insight into the role of data generation in spurring further theorizing. Overall, we contribute empirical evidence and a rich processual understanding of how entrepreneurs articulate complex causal theories. Funding: We appreciate the generous support of the Strategy Research Foundation Dissertation Research Grant Program.

Why and how do workplaces invest in mental health and wellbeing? A systematic review and process tracing study.

In recent years, investment in workplace mental health and wellbeing has grown. However, there is little understanding of how resource allocation decisions are made in such settings. To ensure evaluative research can support resource allocation, a process-based understanding of decision-making would be helpful. In phase one a systematic review of the literature on the implementation of workplace mental health and wellbeing schemes was conducted to draw insights on workplace resource allocation processes. In phase two an in-depth case study of a large company was conducted with interviews with those involved in resource allocation and wellbeing. Interviews were coded and analysed using descriptive and explanatory accounts. The findings from the review and case study were combined and developed into a causal process theory. This study shows that the stages in mental health and wellbeing investment revolve around ensuring organisational buy-in, workforce investment, and continual evaluation. Further work is needed to explore the transferability of the resulting process theory across different types of workplaces. However, it is clear that the features of real world decision-making in workplaces present challenges and opportunities for the research community.

Origins

Abstract Scientific origins are information sources that transmit encoded information signals to receivers. Originary sciences identify information preserving receivers and decode the signals to infer their origins. Paradigmatic cases of scientific origination such as the Big Bang, the origins of species, horizontal gene transfer, the origin of the Polynesian potato, and ideational origins in the history of ideas are analyzed to discover what is common to them ontologically and epistemically. Some causes are not origins. Origination supervenes on causation, but has different properties. The unique properties of origins that causes do not share shield theories of origination from the kind of counterexamples and counterintuitive results that challenge comparable theories of causation. The epistemology of origination may serve as a basis for founding a novel epistemic and methodological division of the sciences into originary historical sciences and causal theoretical sciences.

KindMap: an e-mental health tool to promote the well-being and mental health of people facing infertility—study protocol for a feasibility randomised control trial

IntroductionFertility patients increasingly use web-based and mobile-based apps to access psychosocial care. These digital tools may be a helpful alternative to traditional psychological interventions. Developing and evaluating patient-centred e-mental health...

A causal theory of confirmation for Bayesians

A causal theory of confirmation for Bayesians