This paper deals with causal analysis in the social sciences. We first present a conceptual framework according to which causal analysis is based on a rationale of variation and invariance, and not only on regularity. We then develop a formal framework for causal analysis by means of structural modelling. Within this framework we approach causality in terms of exogeneity in a structural conditional model based which is based on (i) congruence with background knowledge, (ii) invariance under a large (...) variety of environmental changes, and (iii) model fit. We also tackle the issue of confounding and show how latent confounders can play havoc with exogeneity. This framework avoids making untestable metaphysical claims about causal relations and yet remains useful for cognitive and action-oriented goals. (shrink)

Because of the exacting nature of teaching, identifying factors affecting teachers’ mental health and psychological wellbeing are of paramount importance. Parallel with this line of inquiry, the goal of this project was to test a model of psychological wellbeing based on teacher self-efficacy and emotion regulation in an EFL context. To this end, 276 Iranian English teachers participated in this survey. First, the measurement models for the three latent constructs were verified through performing Confirmatory Factor Analysis. Then Structural (...) Equation Modeling was used to test the hypothesized model. SEM outcomes evince that both teacher self-efficacy and emotion regulation were the significant predictors of teachers’ psychological wellbeing, with teacher self-efficacy being a stronger correlate than emotion regulation. The findings offer significant implications for English as a Foreign Language teachers. (shrink)

This paper advances further an ongoing project to understand the history of stellar structure modelling and its inferential practice. It does so by taking a harder look at the data: how it is collected, analysed statistically, and represented in HR diagrams and stellar structure models alike. The focus is ultimately on the sorts of strong observational constraints revealed in the last two decades within the new and expanding field of asteroseismology. It is argued that the typical inferential practices in (...) asteroseismology, while richly loaded with modelling assumptions of their own, do not raise any circularity worries that may compromise the quality or value of the data. (shrink)

We propose a new definition of actual causes, using structural equations to model counterfactuals. We show that the definition yields a plausible and elegant account of causation that handles well examples which have caused problems for other definitions and resolves major difficulties in the traditional account. 1. Introduction2. Causal models: a review2.1Causal models2.2Syntax and semantics3. The definition of cause4. Examples5. A more refined definition6. DiscussionAAppendix: Some Technical IssuesA.1The active causal processA.2A closer look at AC2(b)A.3Causality with infinitely many variablesA.4Causality (...) in nonrecursive models. (shrink)

One way social scientists explain phenomena is by building structural models. These models are explanatory insofar as they manage to perform a recursive decomposition on an initial multivariate probability distribution, which can be interpreted as a mechanism. Explanations in social sciences share important aspects that have been highlighted in the mechanisms literature. Notably, spelling out the functioning the mechanism gives it explanatory power. Thus social scientists should choose the variables to include in the model on the basis (...) of their function in the mechanism. This paper examines the notion of ‘function’ within structural modelling. We argue that ‘functions’ ought to be understood as the theoretical underpinnings of the causes, namely as the role that causes play in the functioning of the mechanism. (shrink)

Rogers & McClelland (R&M) criticize models that rely on structured representations such as categories, taxonomic hierarchies, and schemata, but we suggest that structured models can account for many of the phenomena that they describe. Structured approaches and parallel distributed processing (PDP) approaches operate at different levels of analysis, and may ultimately be compatible, but structured models seem more likely to offer immediate insight into many of the issues that R&M discuss.

We propose a new definition of actual causes, using structural equations to model counterfactuals. We show that the definition yields a plausible and elegant account of causation that handles well examples which have caused problems for other definitions and resolves major difficultiesn in the traditional account.

We propose a new definition of actual causes, using structural equations to model counterfactuals. We show that the definition yields a plausible and elegant account of causation that handles well examples which have caused problems for other definitions and resolves major difficulties in the traditional account.

We propose new definitions of explanation, using structural equations to model counterfactuals. The definition is based on the notion of actual cause, as defined and motivated in a companion article. Essentially, an explanation is a fact that is not known for certain but, if found to be true, would constitute an actual cause of the fact to be explained, regardless of the agent’s initial uncertainty. We show that the definition handles well a number of problematic examples from the literature.

Corporate Governance (CG) issues have driven organisations to set their house right. There is a continual effort by organisations to build on a good framework of policies, not only as an undertaking enforced by a regulatory body, but also to sustain and win. However, these organisations are facing a dilemma in terms of their focus priority. Is it the composition of the board or is it the employee as the stakeholder that has high determining power to reach their goals. The (...) aim of this article is to build upon a structure of enablers of good governance. The paper utilises the Interpretive Structural Modelling (ISM) methodology to understand the mutual influence among the various enablers in such a fashion that the enablers having high driving power and dependency power can be identified. (shrink)

The gap between the metatheoretical inquiries of the analytical philosophy of history, formulated in terms of general principle, and the actual research practices of the historical discipline needs to be bridged. This investigation of the determinants -preconditions, causes, factors, forces - of technological development during the Industrial Revolution makes explicit the range of theoretical instruments used in such studies. The methodologically unavoidable plurality of aspects and perspectives for each concrete inquiry precludes any generally binding model for technological development. Discussion of (...) epistemological presuppositions, by comparing various approaches, can serve to make fully conscious these presuppositions and make them accessible to analysis and criticism. (shrink)

We propose new definitions of (causal) explanation, using structural equations to model counterfactuals. The definition is based on the notion of actual cause, as defined and motivated in a companion article. Essentially, an explanation is a fact that is not known for certain but, if found to be true, would constitute an actual cause of the fact to be explained, regardless of the agent's initial uncertainty. We show that the definition handles well a number of problematic examples from the (...) literature. (shrink)

We propose new definitions of (causal) explanation, using structural equations to model counterfactuals. The definition is based on the notion of actual cause, as defined and motivated in a companion article. Essentially, an explanation is a fact that is not known for certain but, if found to be true, would constitute an actual cause of the fact to be explained, regardless of the agent's initial uncertainty. We show that the definition handles well a number of problematic examples from the (...) literature. 1. Introduction2. Causal models and the definition of actual causality: a review2.1Causal models2.2Syntax and semantics2.3The definition of cause3. Explanation: the basic definition4. Partial explanations and explanatory power5. The general definition6. DiscussionAppendix: the formal definition of causality. (shrink)

An interpretation of Bernard Lonergan's argument for the Exchange Structure Model as it was originally constructed in "For a New Political Economy." The text reveals the steps whereby Lonergan established a fully dynamic foundation for macroeconomics. The author argues that Lonergan's two-circuit approach offers a paradigm shift in the procedures of economic modeling.

It has long been taken for granted that clinical research involving human subjects is ethical only if it holds out the prospect of producing socially valuable knowledge. Recently, this social value requirement has come under scrutiny, with prominent ethicists arguing that the social value requirement cannot be substantiated as an ethical limit on clinical research, and others attempting to offer new support. In this paper, I argue that both criticisms and existing defenses of the social value requirement are predicated on (...) what I call the “transactional model of stakeholder obligations”. I go on to problematize this framework, and to introduce an alternative framework for conceptualizing ethical obligations within clinical research. In defending this framework, which I call the “basic structure model of stakeholder obligations”, I also demonstrate how it provides a stronger grounding for the social value requirement that is not vulnerable to critiques grounded in the transactional model. (shrink)

A model of analogical mapping is proposed that uses five principles to generate consistent and conflicting hypotheses regarding assignments of elements of a source domain to analogous elements of a target domain. The principles follow the fine conceptual structure of the domains. The principles are: (1) the principle of proportional analogy; (2) the principle of mereological analogy, (3) the principle of chain reinforcement; (4) the principle of transitive reinforcement; and (5) the principle of mutual inconsistency. A constraint-satisfaction network is used (...) to find the set of assignments that preserves the greatest relational structure of the source. In contrast to the model proposed here, most models of analogical mapping use only the principle of proportional analogy. The use of many principles is shown to be superior in that it permits smoother integration of pragmatic factors and results in a more efficient mapping process. (shrink)

A study of stage structured model of fish population is presented. This model focuse on the anchovy population in the Bay of Biscay (Engraulis encrasicolus L.) is presented. The method of study is based on an intermediate complexity mathematical model, taking into account the spatialisation, the environmental conditions and the stage-structure of the fishes. First, to test the model, we show mathematical properties, such as unicity of the solution of structural stability. Then we provide numerical simulations, to validate the (...) model and to test the dynamics according to the variations of the parameters. (shrink)

Abstract: The Pull Bayesian Significance Test (FBST) for precise hy- potheses is applied to a Multivariate Normal Structure (MNS) model. In the FBST we compute the evidence against the precise hypothesis. This evi- dence is the probability of the Highest Relative Surprise Set (HRSS) tangent to the sub-manifold (of the parameter space) that defines the null hypothesis. The MNS model we present appears when testing equivalence conditions for genetic expression measurements, using micro-array technology.

Marginal structural models can be used to estimate the causal effect of a potentially time-varying treatment in the presence of time-dependent confounding via weighted regression. The standard approach of using inverse probability of treatment weighting can be sensitive to model misspecification and lead to high-variance estimates due to extreme weights. Various methods have been proposed to partially address this, including covariate balancing propensity score to mitigate treatment model misspecification, and truncation and stabilized-IPTW to temper extreme weights. In this (...) article, we present kernel optimal weighting, a convex-optimization-based approach that finds weights for fitting the MSMs that flexibly balance time-dependent confounders while simultaneously penalizing extreme weights, directly addressing the above limitations. We further extend KOW to control for informative censoring. We evaluate the performance of KOW in a simulation study, comparing it with IPTW, sIPTW, and CBPS. We demonstrate the use of KOW in studying the effect of treatment initiation on time-to-death among people living with human immunodeficiency virus and the effect of negative advertising on elections in the United States. (shrink)

I will present two different applications - Dual PECCS and the TCL reasoning framework - addressing some crucial aspects of commonsense reasoning (namely: dealing with typicality effects and with the problem of commonsense compositionality) in a way that is integrated or compliant with different cognitive architectures. In doing so I will show how such aspects are better dealt with at different levels of representation and will discuss the adopted solution to integrate such representational layers.

The projective plane of Baldwin 695) is model complete in a language with additional constant symbols. The infinite rank bicolored field of Poizat 1339) is not model complete. The finite rank bicolored fields of Baldwin and Holland 371; Notre Dame J. Formal Logic , to appear) are model complete. More generally, the finite rank expansions of a strongly minimal set obtained by adding a ‘random’ unary predicate are almost strongly minimal and model complete provided the strongly minimal set is ‘well-behaved’ (...) and admits ‘exactly rank k formulas’. The last notion is a geometric condition on strongly minimal sets formalized in this paper. (shrink)

Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence, business, epidemiology, social science and economics.

An interpretation of Bernard Lonergan's argument for the Exchange Structure Model as it was originally constructed in "For a New Political Economy." The text reveals the steps whereby Lonergan established a fully dynamic foundation for macroeconomics. The author argues that Lonergan's two-circuit approach offers a paradigm shift in the procedures of economic modeling.

In this article, I critically reassess Iris Marion Young's late works, which centre on the distinction between liability and social connection responsibility. I concur with Young's diagnosis that structural injustices call for a new conception of responsibility, but I reject several core assumptions that underpin her distinction between two models and argue for a different way of conceptualising responsibility to address structural injustices. I show that Young's categorical separation of guilt and responsibility is not supported by the (...) writings of Hannah Arendt, which Young draws on, and that it is also untenable on independent systematic grounds. Furthermore, I argue that several of Young's other criteria fail to clearly demarcate two distinct phenomena. I therefore propose to transcend Young's distinction between two models in favour of a related, but conceptually different distinction between two forms of responsibility: interactional and structural. Embracing this terminology facilitates the conceptualisation of the general features of responsibility that are shared by both forms, including their retrospective and prospective time-direction and their applicability to individual, joint and group agency. The distinction between interactional and structural responsibility also yields a more compelling general account of the role of background structures, and of blame within ascriptions of political responsibility. (shrink)

In 1974, John Maynard Smith wrote in his little book Models in Ecology, A theory of ecology must make statements about ecosystems as a whole, as well as about particular species at particular times, and it must make statements that are true for many species and not just for one… For the discovery of general ideas in ecology, therefore, different kinds of mathematical description, which may be called models, are called for. Whereas a good simulation should include as (...) much detail as possible, a good model should include as little as possible. (1974. (shrink)

The focus in the literature on scientific explanation has shifted in recent years towards model-based approaches. In recent work, Alisa Bokulich has argued that idealization has a central role to play in explanation. Bokulich claims that certain highly-idealized, structural models can be explanatory, even though they are not considered explanatory by causal, mechanistic, or covering law accounts of explanation. This paper focuses on Bokulich’s account in order to make the more general claim that there are problems with maintaining (...) that a structural criterion can capture the way that highly-idealized models explain. This paper examines Bokulich’s claim that the structural model explanation of quantum wavefunction scarring, featuring semiclassical mechanics, is deeper than the explanation provided by the local quantum model. The challenge for Bokulich is to show that the semiclassical model answers a wider range of w-questions, as this is her method of assessing structural information. I look at two reasonable approaches employing w-questions, and I argue that neither approach is ultimately satisfactory. Because structural similarity has preferences for more fundamental models, I argue that the local quantum model provides explanations that at least as deep as the semiclassical ones. The criterion either wrongly identifies all models as explanatory, or prefers models from fundamental theory. Either way, it cannot capture the way that highly-idealized models explain. (shrink)

In this paper we argue that structural explanations are an effective way of explaining well known relativistic phenomena like length contraction and time dilation, and then try to understand how this can be possible by looking at the literature on scientific models. In particular, we ask whether and how a model like that provided by Minkowski spacetime can be said to represent the physical world, in such a way that it can successfully explain physical phenomena structurally. We conclude (...) by claiming that a partial isomorphic approach to scientific representation can supply an answer only if supplemented by a robust injection of pragmatic factors. (shrink)