Within the causal modeling literature, debates about the Causal Faithfulness Condition have concerned whether it is probable that the parameters in causal models will have values such that distinct causal paths will cancel. As the parameters in a model are fixed by the probability distribution over its variables, it is initially puzzling what it means to assign probabilities to these parameters. I propose that to assign a probability to a parameter in a model is to treat that parameter as a (...) function of a variable in an augmented model. By combining this proposal with widely adopted principles regarding which variables must be included in a model, I argue that the various proposed counterexamples to CFC involving coordinated parameters are not genuine counterexamples. I then consider the cases in which CFC fails due not to coordination, but by coincidence, and propose explanatory and predictive bases for ruling out such coincidences without presuming that they are improbable. The aim of the proposed defenses is not to show that CFC never fails, but rather to argue that its use in a particular context may be defended using general modeling assumptions rather than by relying on claims about how often it fails. (shrink)

A common strategy for simplifying complex systems involves partitioning them into subsystems whose behaviors are roughly independent of one another at shorter timescales. Dynamic causal models clarify how doing so reveals a system’s nonequilibrium causal relationships. Here I use these models to elucidate the idealizations and abstractions involved in representing a system at a timescale. The models reveal that key features of causal representations—such as which variables are exogenous—may vary with the timescale at which a system is considered. This has (...) implications for debates regarding which systems can be represented causally. (shrink)

Markus (2021) argues that the causal modelling frameworks of Pearl and Rubin are not ‘strongly equivalent’, in the sense of saying ‘the same thing in different ways’. Here I rebut Markus’ arguments against strong equivalence. The differences between the frameworks are best illuminated not by appeal to their causal semantics, but rather reflect pragmatic modelling choices.

A cause may influence its effect via multiple paths. Paradigmatically (Hesslow [1974]), taking birth control pills both decreases one’s risk of thrombosis by preventing pregnancy and increases it by producing a blood chemical. Building on Pearl ([2001]), I explicate the notion of a path-specific effect. Roughly, a path-specific effect of C on E via path P is the degree to which a change in C would change E were they to be transmitted only via P. Facts about such effects may (...) be gleaned from the structural equations commonly used to represent the causal relationships among variables. I contrast my analysis of the Hesslow case with those given by theorists of probabilistic causality, who mistakenly link it to issues of causal heterogeneity, token-causation and indeterminism. The reason probabilistic theories misdiagnose this case is that they pay inadequate attention to the structural relationships among variables. (shrink)

Discussions of the causal status of race focus on the question of whether race itself can be experimentally manipulated. Yet many experiments testing for racial discrimination do not manipulate race, but rather a signal by which race influences an outcome. Such signal manipulations are easily formalized, though contexts of discrimination introduce significant philosophical complications. Whether a signal counts as a signal for race is not merely a causal question, but depends on sociological and normative issues regarding discrimination. The notion of (...) signal manipulation enables one to take these issues into account while still using causal counterfactual tests to detect discrimination. The analysis provided here is compatible with social constructivism and helps differentiate between cases in which it is more or less fruitful to model race causally. (shrink)

Dynamical models of cognition have played a central role in recent cognitive science. In this paper, we consider a common strategy by which dynamical models describe their target systems neither as purely static nor as purely dynamic, but rather using a hybrid approach. This hybridity reveals how dynamical models involve representational choices that are important for understanding the relationship between dynamical and non-dynamical representations of a system.

In a recent paper, Brandon and Nijhout argue against genic selectionism—the thesis, roughly, that evolutionary processes are best understood from the gene’s-eye point of view—by presenting a case in which genic models of selection allegedly make predictions that conflict with the (correct) predictions of higher-level genotypic selection models. Their argument, if successful, would refute the widely held belief that genic models and higher-level models are predictively equivalent. Here, I argue that Brandon and Nijhout fail to demonstrate that the models make (...) incompatible predictions. (shrink)

This book explores the philosophy of love through the thought and life of Rabbi Akiva ben Joseph. Readers of the Talmud are introduced to Rabbi Akiva through the iconic story of his love for his wife Rachel. From this starting point, Naftali Rothenberg conducts a thorough examination of the harmonious approach to love in the obstacle-laden context of human reality. Discussing the deterioration of passion into simple lust, the ability to contend with suffering and death, and so forth, Rothenberg (...) addresses the deepest and most pressing questions about human love. The readings and observations offered here allow readers to acquire the wisdom of love-not merely as an assemblage of theoretical arguments and abstract statements, but as an analysis of the internal contradictions and difficulties revealed in the context of attempts to realize and implement harmonious love. (shrink)

Some recent accounts of constitutive relevance have identified mechanism components with entities that are causal intermediaries between the input and output of a mechanism. I argue that on such accounts there is no distinctive inter-level form of mechanistic explanation and that this highlights an absence in the literature of a compelling argument that there are such explanations. Nevertheless, the entities that these accounts call ‘components’ do play an explanatory role. Studying causal intermediaries linking variables Xand Y provides knowledge of the (...) counterfactual conditions under which X will continue to bring about Y. This explanatory role does not depend on whether intermediate variables count as components. The question of whether there are distinctively mechanistic explanations remains open. (shrink)

Causal representations are distinguished from non-causal ones by their ability to predict the results of interventions. This widely-accepted view suggests the following adequacy condition for causal models: a causal model is adequate only if it does not contain variables regarding which it makes systematically false predictions about the results of interventions. Here I argue that this condition should be rejected. For a class of equilibrium systems, there will be two incompatible causal models depending on whether one intervenes upon a certain (...) variable to fix its value, or ‘lets go’ of the variable and allows it to vary. The latter model will fail to predict the result of interventions on the let-go-of variable. I argue that there is no basis for preferring one of these models to the other, and thus that models failing to predict interventions on particular variables can be just as adequate as those making no such false predictions. This undermines a key argument (Dash in Caveats for causal reasoning with equilibrium models. University of Pittsburgh. PhD thesis, 2003) against relying upon causal models inferred from equilibrium data. (shrink)

The book Chronicle of Separation is an attempt to write on Derrida, to Derrida and from Derrida on the basis of a pathetic experience, which, in various ways, describes and enacts the pathetic experience of deconstruction itself. The book tackles the weight of emotions that is at the heart of deconstructive reading, treating deconstruction's weak, fragile and parasitic mode of thinking as a deconstruction of emotion, on emotion and as emotion. Chronicle of Separation examines these themes beginning with a descriptive (...) and an analytic reading of Derrida's Memoirs: For Paul de Man and The Post Card, as embodiments of deconstruction's melancholic friendship which inscribes its disillusioned love in what it calls the 'postal condition'. The book then moves on to a feminization of Derrida, experimenting in different modes of writing. It firstly discusses Fred Zinneman's film Julia about a mournful friendship between women. Then it performs a deconstructive meditation on the anorexic person suggesting that anorexia constitutes a paradoxical embodiment of deconstruction. The concluding chapter presents a complete incorporation of Derrida into a fictional text that re-writes the biblical Book of Ruth. (shrink)

The essay examines Scholem's letter-confession on the Hebrew language addressed to Rosenzweig from two perspectives hitherto ignored in the ongoing interpretative consideration of this document: Scholem's repression of the literary space and his consequent exclusion of madness. The essay follows several threads in Derrida's own ‘internal’ reading of the letter, and leans on other Derridean writings such as The Monolingualism of the Other, Schibboleth: For Paul Celan and ‘Cogito and the History of Madness’ in order to suggest two distinct encounters (...) between Derrida and Scholem: In the first encounter, Scholem reads Derrida and proves to be deconstructing his own notions of secular and profane Hebrew, while fighting in vain for his sanity by clinging to liturgical practices against the grain of an ongoing ‘actualization’, politicization or else fictionalization of the sacred language. In the second encounter, it is Derrida who reads Scholem. By transforming the particular conditions of possibility of Hebrew into general conditions of possibility of every language contaminated by a theological-political tension, Derrida contributes some important insights for contemporary Hebrew speakers. (shrink)

ḥeleḳ 1. Dine birkot ha-nehenin--ḥeleḳ 2. Ṭohorat ha-lashon ṿeha-nefesh--ḥeleḳ 3. Dine teḥilat ha-yom--ḥeleḳ 4. Dine tefilat ha-shaḥar--ḥeleḳ 5. Neśiʼat-kapayim ṿe-taḥanun--ḥeleḳ 6. Dine ḳeriʼat ha-Torah--ḥeleḳ 7. Sheʼar tefilot ha-yom--ḥeleḳ 8. Tefilah be-Shabat uve-moʻed--ḥeleḳ 9. Dine Yamim Noraʼim--ḥeleḳ 10. Dine Ḥanukah u-Furim--ḥeleḳ 11. Mafteaḥ kelali meforaṭ.

Mechanist philosophers have examined several strategies scientists use for discovering causal mechanisms in neuroscience. Findings about the anatomical organization of the brain play a central role in several such strategies. Little attention has been paid, however, to the use of network analysis and causal modeling techniques for mechanism discovery. In particular, mechanist philosophers have not explored whether and how these strategies incorporate information about the anatomical organization of the brain. This paper clarifies these issues in the light of the distinction (...) between structural, functional and effective connectivity. Specifically, we examine two quantitative strategies currently used for causal discovery from functional neuroimaging data: dynamic causal modeling and probabilistic graphical modeling. We show that dynamic causal modeling uses findings about the brain’s anatomical organization to improve the statistical estimation of parameters in an already specified causal model of the target brain mechanism. Probabilistic graphical modeling, in contrast, makes no appeal to the brain’s anatomical organization, but lays bare the conditions under which correlational data suffice to license reliable inferences about the causal organization of a target brain mechanism. The question of whether findings about the anatomical organization of the brain can and should constrain the inference of causal networks remains open, but we show how the tools supplied by graphical modeling methods help to address it. (shrink)

This interview with Michal Ben-Naftali from March 2004 is one of Derrida's last. It begins with the question of the relationship between love, law, and justice and then moves on to discuss everything from the secret, hospitality, friendship, sacrifice, pardon and psychoanalysis to the relationship between deconstruction and melancholy.

Is Bayesian decision theory a panacea for many of the problems in epistemology and the philosophy of science, or is it philosophical snake-oil? For years a debate had been waged amongst specialists regarding the import and legitimacy of this body of theory. Mark Kaplan had written the first accessible and non-technical book to address this controversy. Introducing a new variant on Bayesian decision theory the author offers a compelling case that, while no panacea, decision theory does in fact have the (...) most profound consequences for the way in which philosophers think about inquiry, criticism and rational belief. The new variant on Bayesian theory is presented in such a way that a non-specialist will be able to understand it. The book also offers new solutions to some classic paradoxes. It focuses on the intuitive motivations of the Bayesian approach to epistemology and addresses the philosophical worries to which it has given rise. (shrink)

This article focuses on the location of the duty of loyalty—a unique legal norm in Common Law jurisdictions—both actual and desirable, on the continuum between rules and standards. A rule is a relatively ‘closed’ technical norm, at a high level of specificity; it requires little judicial discretion. A standard is an ‘open’ norm, with a greater degree of flexibility, that requires the exercise of discretion. The insights from this jurisprudential perspective are used to reveal the preferred way for further developing (...) the duty of loyalty. The article explains that ‘loyalty,’ intuitively classified as a ‘pure’ standard, has been reconstructed over time as more specific rules. Moreover, it suggests that, ideally, this movement should continue; namely, when applying loyalty to a specific case, courts should include informative content that would promote predictability. It then illustrates that, unfortunately, this road is not always taken by the courts. A decision to retain loyalty as an ad hoc standard, or an inverse attempt to delineate the boundaries of this norm, has implications on the certainty, consistency, and ethical content of the law. Considering that this duty spreads across different legal fields, personal and commercial, the significance of this discussion becomes all the more evident. (shrink)

Is Bayesian decision theory a panacea for many of the problems in epistemology and the philosophy of science, or is it philosophical snake-oil? For years a debate had been waged amongst specialists regarding the import and legitimacy of this body of theory. Mark Kaplan had written the first accessible and non-technical book to address this controversy. Introducing a new variant on Bayesian decision theory the author offers a compelling case that, while no panacea, decision theory does in fact have the (...) most profound consequences for the way in which philosophers think about inquiry, criticism and rational belief. The new variant on Bayesian theory is presented in such a way that a non-specialist will be able to understand it. The book also offers new solutions to some classic paradoxes. It focuses on the intuitive motivations of the Bayesian approach to epistemology and addresses the philosophical worries to which it has given rise. (shrink)

We argue that dynamical and mathematical models in systems and cognitive neuro- science explain (rather than redescribe) a phenomenon only if there is a plausible mapping between elements in the model and elements in the mechanism for the phe- nomenon. We demonstrate how this model-to-mechanism-mapping constraint, when satisfied, endows a model with explanatory force with respect to the phenomenon to be explained. Several paradigmatic models including the Haken-Kelso-Bunz model of bimanual coordination and the difference-of-Gaussians model of visual receptive fields are (...) explored. (shrink)

The central aim of this paper is to shed light on the nature of explanation in computational neuroscience. I argue that computational models in this domain possess explanatory force to the extent that they describe the mechanisms responsible for producing a given phenomenon—paralleling how other mechanistic models explain. Conceiving computational explanation as a species of mechanistic explanation affords an important distinction between computational models that play genuine explanatory roles and those that merely provide accurate descriptions or predictions of phenomena. It (...) also serves to clarify the pattern of model refinement and elaboration undertaken by computational neuroscientists. (shrink)