This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and (...) made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. (shrink)

Specifying accurate informative prior distributions is a question of carefully selecting studies that comprise the body of comparable background knowledge. Psychological research, however, consists of studies that are being conducted under different circumstances, with different samples and varying instruments. Thus, results of previous studies are heterogeneous, and not all available results can and should contribute equally to an informative prior distribution. This implies a necessary weighting of background information based on the similarity of the previous studies to (...) the focal study at hand. Current approaches to account for heterogeneity by weighting informative prior distributions, such as the power prior and the meta-analytic predictive prior are either not easily accessible or incomplete. To complicate matters further, in the context of Bayesian multiple regression models there are no methods available for quantifying the similarity of a given body of background knowledge to the focal study at hand. Consequently, the purpose of this study is threefold. We first present a novel method to combine the aforementioned sources of heterogeneity in the similarity measure ω. This method is based on a combination of a propensity-score approach to assess the similarity of samples with random- and mixed-effects meta-analytic models to quantify the heterogeneity in outcomes and study characteristics. Second, we show how to use the similarity measure ωas a weight for informative prior distributions for the substantial parameters in Bayesian multiple regression models. Third, we investigate the performance and the behavior of the similarity-weighted informative prior distribution in a comprehensive simulation study, where it is compared to the normalized power prior and the meta-analytic predictive prior. The similarity measure ω and the similarity-weighted informative prior distribution as the primary results of this study provide applied researchers with means to specify accurate informative prior distributions. (shrink)

The purpose of this article is to present and discuss some of the best practices of financial industry, in three emerging economies: Colombia, Ecuador, and Peru. The main thesis is that, notwithstanding the importance of certain specific deficiencies, such as an inadequate regulatory context or the lack of financial education among the population, the main factor that explains the low banking levels in emerging and developing economies, affecting mostly lower-income segments, is the use of inefficient financial service distribution models. (...) In connection with this thesis, we will try to show that traditional financial institutions, both in developing countries and in the advanced economies have a special social responsibility to help create an efficient financial system that makes saving and borrowing instruments available to the greatest possible number of citizens. (shrink)

Do participants bring their own priors to an experiment? If so, do they share the same priors as the researchers who design the experiment? In this article, we examine the extent to which self-generated priors conform to experimenters’ expectations by explicitly asking participants to indicate their own priors in estimating the probability of a variety of events. We find in Study 1 that despite being instructed to follow a uniform distribution, participants appear to have used their own priors, which (...) deviated from the given instructions. Using subjects’ own priors allows us to account better for their responses rather than merely to test the accuracy of their estimates. Implications for the study of judgment and decision making are discussed. (shrink)

BackgroundBayesian estimation with informative priors permits updating previous findings with new data, thus generating cumulative knowledge. To reduce subjectivity in the process, the present study emphasizes how to systematically weigh and specify informative priors and highlights the use of different aggregation methods using an empirical example that examined whether observed mother-adolescent positive and negative interaction behavior mediate the associations between maternal and adolescent internalizing symptoms across early to mid-adolescence in a 3-year longitudinal multi-method design.MethodsThe sample consisted of 102 mother-adolescent dyads. (...) Mothers and adolescents reported on their internalizing symptoms and their interaction behaviors were observed during a conflict task. We systematically searched for previous studies and used an expert-informed weighting system to account for their relevance. Subsequently, we aggregated the priors using three methods: linear pooling, logarithmic pooling, and fitting a normal distribution to the linear pool by means of maximum likelihood estimation. We compared the impact of the three differently specified informative priors and default priors on the prior predictive distribution, shrinkage, and the posterior estimates.ResultsThe prior predictive distributions for the three informative priors were quite similar and centered around the observed data mean. The shrinkage results showed that the logarithmic pooled priors were least affected by the data. Most posterior estimates were similar across the different priors. Some previous studies contained extremely specific information, resulting in bimodal posterior distributions for the analyses with linear pooled prior distributions. The posteriors following the fitted normal priors and default priors were very similar. Overall, we found that maternal, but not adolescent, internalizing symptoms predicted subsequent mother-adolescent interaction behavior, whereas negative interaction behavior seemed to predict subsequent internalizing symptoms. Evidence regarding mediation effects remained limited.ConclusionA systematic search for previous information and an expert-built weighting system contribute to a clear specification of power priors. How information from multiple previous studies should be included in the prior depends on theoretical considerations, and may also be affected by pragmatic considerations regarding the impact of the previous results at hand. (shrink)

Bayesian approaches for estimating multilevel latent variable models can be beneficial in small samples. Prior distributions can be used to overcome small sample problems, for example, when priors that increase the accuracy of estimation are chosen. This article discusses two different but not mutually exclusive approaches for specifying priors. Both approaches aim at stabilizing estimators in such a way that the Mean Squared Error of the estimator of the between-group slope will be small. In the first approach, the MSE (...) is decreased by specifying a slightly informative prior for the group-level variance of the predictor variable, whereas in the second approach, the decrease is achieved directly by using a slightly informative prior for the slope. Mathematical and graphical inspections suggest that both approaches can be effective for reducing the MSE in small samples, thus rendering them attractive in these situations. The article also discusses how these approaches can be implemented in Mplus. (shrink)

This study investigated the impact of three prior distributions: matched, standard vague, and hierarchical in Bayesian estimation parameter recovery in two and one parameter models. Two Bayesian estimation methods were utilized: Markov chain Monte Carlo (MCMC) and the relatively new, Variational Bayesian (VB). Conditional (CML) and Marginal Maximum Likelihood (MML) estimates were used as baseline methods for comparison. Vague priors produced large errors or convergence issues and are not recommended. For both MCMC and VB, the hierarchical and matched priors (...) showed the lowest root mean squared errors (RMSEs) for ability estimates; RMSEs of difficulty estimates were similar across estimation methods. For the standard errors (SEs), MCMC-hierarchical displayed the largest values across most conditions. SEs from the VB estimation were among the lowest in all but one case. Overall, VB-hierarchical, VB-matched, and MCMC-matched performed best. VB with hierarchical priors are recommended in terms of their accuracy, and cost and (subsequently) time effectiveness. (shrink)

The original development of the formalism of quantum mechanics involved the study of isolated quantum systems in pure states. Such systems fail to capture important aspects of the warm, wet, and noisy physical world which can better be modelled by quantum statistical mechanics and local quantum field theory using mixed states of continuous systems. In this context, we need to be able to compute quantum probabilities given only partial information. Specifically, suppose that B is a set of operators. This set (...) need not be a von Neumann algebra. Simple axioms are proposed which allow us to identify a function which can be interpreted as the probability, per unit trial of the information specified by B, of observing the (mixed) state of the world restricted to B to be σ when we are given ρ – the restriction to B of a prior state. This probability generalizes the idea of a mixed state (ρ) as being a sum of terms (σ) weighted by probabilities. The unique function satisfying the axioms can be defined in terms of the relative entropy. The analogous inference problem in classical probability would be a situation where we have some information about the prior distribution, but not enough to determine it uniquely. In such a situation in quantum theory, because only what we observe should be taken to be specified, it is not appropriate to assume the existence of a fixed, definite, unknown prior state, beyond the set B about which we have information. The theory was developed for the purposes of a fairly radical attack on the interpretation of quantum theory, involving many-worlds ideas and the abstract characterization of observers as finite information-processing structures, but deals with quantum inference problems of broad generality. (shrink)

Establishing reasonable, prior distributions remains a significant obstacle for the construction of probabilistic expert systems. Human assessment of chance is often relied upon for this purpose, but this has the drawback of being inconsistent with axioms of probability. This article advances a method for extracting a coherent distribution of probability from human judgment. The method is based on a psychological model of probabilistic reasoning, followed by a correction phase using linear programming.

The current paper highlights a new, interactive Shiny App that can be used to aid in understanding and teaching the important task of conducting a prior sensitivity analysis when implementing Bayesian estimation methods. In this paper, we discuss the importance of examining prior distributions through a sensitivity analysis. We argue that conducting a prior sensitivity analysis is equally important when so-called diffuse priors are implemented as it is with subjective priors. As a proof of concept, we conducted (...) a small simulation study, which illustrates the impact of priors on final model estimates. The findings from the simulation study highlight the importance of conducting a sensitivity analysis of priors. This concept is further extended through an interactive Shiny App that we developed. The Shiny App allows users to explore the impact of various forms of priors using empirical data. We introduce this Shiny App and thoroughly detail an example using a simple multiple regression model that users at all levels can understand. In this paper, we highlight how to determine the different settings for a prior sensitivity analysis, how to visually and statistically compare results obtained in the sensitivity analysis, and how to display findings and write up disparate results obtained across the sensitivity analysis. The goal is that novice users can follow the process outlined here and work within the interactive Shiny App to gain a deeper understanding of the role of prior distributions and the importance of a sensitivity analysis when implementing Bayesian methods. The intended audience is broad and can include those with limited exposure to Bayesian methods or the specific model presented here. (shrink)

What is it like to be an octopus, one of those eight-armed, infinitely flexible sea creatures with a nervous system distributed over head, eyes and arms? One interesting approach is to argue that octopuses, because of their distributed nervous systems, are likely to possess disunified consciousness (Carls-Diamante 2017). However, this supposed isomorphism between a “unified” nervous system and “unified” consciousness is problematic, since the term “unity” is taken as a “given” even though it is far from clear what it means. (...) I will argue that explaining the structure of consciousness requires a prior explanation in terms of how it is achieved by the organism through sensorimotor integration. On this account, the structure of an organism’s consciousness is explained partly by what the external world is like, and partly by how the organism’s body, senses and nervous system enable the organism to interact with the external world. (shrink)

Elicitation methods aim to build participants' distributions about a parameter of interest. In most elicitation studies this parameter is rarely known in advance and hinders an objective comparison between elicitation methods. In two experiments, participants were first presented with a fixed random sequence of images and numbers and subsequently their subjective distributions of percentages of one of those numbers was elicited. Importantly, the true percentage was set in advance. The first experiment tested whether receiving instructions as to the elicitation method (...) would assist in estimating a true value more accurately than receiving no instructions and whether accuracy was determined by the numerical skills of the participants. The second experiment sought to compare the elicitation method used in the first experiment with a variation of a graphical elicitation method. The results indicate that (i) receiving instructions as to the elicitation method does assist in producing estimates closer to a true percentage value, (ii) the level of numerical skills does not play a part in the accuracy of the estimation (Experiment 1), and (iii) although the average estimates of the betting and graphical method are not significantly different, the betting method leads to more precise estimations than the graphical method (Experiment 2). Both studies featured statistical procedures (functional data analysis and a novel clustering technique) not considered in past research on the elicitation of subjective distributions. The implications of these results are discussed in relation to a recent key study. (shrink)

Acts are functions from states of nature into finite-support distributions over a set of ‘deterministic outcomes’. We characterize preference relations over acts which have a numerical representation by the functional J(f)=min>∫u∘ f dP¦PϵC where f is an act, u is a von Neumann-Morgenstern utility over outcomes, and C is a closed and convex set of finitely additive probability measures on the states of nature. In addition to the usual assumptions on the preference relation as transitivity, completeness, continuity and monotonicity, we (...) assume uncertainty aversion and certainty-independence. The last condition is a new one and is a weakening of the classical independence axiom: It requires that an act f is preferred to an act g if and only if the mixture of f and any constant act h is preferred to the same mixture of g and h. If non-degeneracy of the preference relation is also assumed, the convex set of priors C is uniquely determined. Finally, a concept of independence in case of a non-unique prior is introduced. (shrink)

We discuss the role of prior authorization (PA) in supporting patient-centered care (PCC) by directing health system resources and thus the ability to better meet the needs of individual patients. We begin with an account of PCC as a standard that should be aimed for in patient care. In order to achieve widespread PCC, appropriate resource management is essential in a healthcare system. This brings us to PA, and we present an idealized view of PA in order to argue (...) how at its best, it can contribute to the provision of PCC. PA is a means of cost saving and as such it has mixed success. The example of the US demonstrates how implementation of PA has increased health inequalities whereas best practice has the potential to reduce them. In contrast, systems of universal coverage, like those in Europe, may use the cost savings of PA to better address individuals' care and PCC. The conclusion we offer therefore is an optimistic one, pointing towards areas of supportive overlap between PCC and PA where usually the incongruities are most evident. (shrink)

Bayesian methods have become among the most popular methods in phylogenetics, but theoretical opposition to this methodology remains. After providing an introduction to Bayesian theory in this context, I attempt to tackle the problem mentioned most often in the literature: the “problem of the priors”—how to assign prior probabilities to tree hypotheses. I first argue that a recent objection—that an appropriate assignment of priors is impossible—is based on a misunderstanding of what ignorance and bias are. I then consider different (...) methods of assigning prior probabilities to trees. I argue that priors need to be derived from an understanding of how distinct taxa have evolved and that the appropriate evolutionary model is captured by the Yule birth–death process. This process leads to a well-known statistical distribution over trees. Though further modifications may be necessary to model more complex aspects of the branching process, they must be modifications to parameters in an underlying Yule model. Ignoring these Yule priors commits a fallacy leading to mistaken inferences both about the trees themselves and about macroevolutionary processes more generally. (shrink)

Using belief elicitation, the paper investigates the process of belief formation and evolution in a signaling game in which a common prior is not induced. Both prior and posterior beliefs of Receivers about Senders’ types are elicited, as well as beliefs of Senders about Receivers’ strategies. In the experiment, subjects often start with diffuse uniform beliefs and update them in view of observations. However, the speed of updating is influenced by the strength of initial beliefs. An interesting result (...) is that beliefs about the prior distribution of types are updated slower than posterior beliefs, which incorporate Senders’ strategies. In the medium run, for some specifications of game parameters, this leads to outcomes being significantly different from the outcomes of the game in which a common prior is induced. It is also shown that elicitation of beliefs does not considerably change the pattern of play in this game. (shrink)

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The paper shows that in the Art of Thinking (The Port Royal Logic) Arnauld and Nicole introduce a new way to state the truth-conditions for categorical propositions. The definition uses two new ideas: the notion of distributive or, as they call it, universal term, which they abstract from distributive supposition in medieval logic, and their own version of what is now called a conservative quantifier in general quantification theory. Contrary to the interpretation of Jean-Claude Parienté and others, the truth-conditions do (...) not require the introduction of a new concept of ‘indefinite’ term restriction because the notion of conservative quantifier is formulated in terms of the standard notion of term intersection. The discussion shows the following. Distributive supposition could not be used in an analysis of truth because it is explained in terms of entailment, and entailment in terms of truth. By abstracting from semantic identities that underlie distribution, the new concept of distributive term is definitionally prior to truth and can, therefore, be used in a non-circular way to state truth-conditions. Using only standard restriction, the Logic’s truth-conditions for the categorical propositions are stated solely in terms of (1) universal (distributive) term, (2) conservative quantifier, and (3) affirmative and negative proposition. It is explained why the Cartesian notion of extension as a set of ideas is in this context equivalent to medieval and modern notions of extension. (shrink)

In this article, we consider estimation of the parameters of a generalized Pareto distribution and some lifetime indices such as those relating to reliability and hazard rate functions when the failure data are progressive first-failure censored. Both classical and Bayesian techniques are obtained. In the Bayesian framework, the point estimations of unknown parameters under both symmetric and asymmetric loss functions are discussed, after having been estimated using the conjugate gamma and discrete priors for the shape and scale parameters, respectively. (...) In addition, both exact and approximate confidence intervals as well as the exact confidence region for the estimators are constructed. A practical example using a simulated data set is analyzed. Finally, the performance of Bayes estimates is compared with that of maximum likelihood estimates through a Monte Carlo simulation study. (shrink)

The philosophical debate on secession has hitherto revolved primarily around the question of self-determination rather than that of distributive justice. Normative theorists of secession have approached the question of secession mostly in terms of the right that the secessionist group has to secede. Much less attention has been paid to the extent and the nature of obligations or duties that the seceding group might have toward the group it is leaving behind. At best, secession theorists have introduced clauses to the (...) effect that secession should not undermine the remainder state’s viability nor violate prior arrangements of reciprocal cooperation. While these clauses certainly reflect a certain concern for distributive justice, I argue that they are insufficient in two respects: they are problematically minimal in what they require, and the justification given for these clauses accounts only for part of the normative picture. In this paper, I address these two shortcomings by arguing that the seceding group might have significant duties of distributive justice toward the remainder group, and that these duties are associative in nature and stem from a concern to secure non-domination within the pre-secession polity. What is gained from my non-domination account, then, is that it is analytically more comprehensive and normatively more accurate. In arguing for claims and, the paper contributes both to the debate on secession as well as to the conceptualization of associative duties and of non-domination. (shrink)

Although Bayesian methods are widely used in phylogenetic systematics today, the foundations of this methodology are still debated among both biologists and philosophers. The Bayesian approach to phylogenetic inference requires the assignment of prior probabilities to phylogenetic trees. As in other applications of Bayesian epistemology, the question of whether there is an objective way to assign these prior probabilities is a contested issue. This paper discusses the strategy of constraining the prior probabilities of phylogenetic trees by means (...) of the Principal Principle. In particular, I discuss a proposal due to Velasco (Biol Philos 23:455–473, 2008) of assigning prior probabilities to tree topologies based on the Yule process. By invoking the Principal Principle I argue that prior probabilities of tree topologies should rather be assigned a weighted mixture of probability distributions based on Pinelis’ (P Roy Soc Lond B Bio 270:1425–1431, 2003) multi-rate branching process including both the Yule distribution and the uniform distribution. However, I argue that this solves the problem of the priors of phylogenetic trees only in a weak form. (shrink)

A traditional ethic of medicine asserts that physicians have special obligations to individual patients with whom they have a clinical relationship. Contemporary trends in US healthcare financing like bundled payments seem to threaten traditional conceptions of special obligations of individual physicians to individual patients because their population-based focus sets a tone that seems to emphasise responsibilities for groups of patients by groups of physicians in an organisation. Prior to undertaking a cogent debate about the fate and normative weight of (...) special obligations and a traditional ethic for contemporary healthcare, we need a deeper examination of what the traditional ethic of special obligations really means. Here we offer a conception of ‘doubly distributed’ special obligations. Physicians and similarly minded healing professionals abiding by a traditional ethic have always spread their devotion and attention across multiple patients and have shared responsibilities with physician and non-physician colleagues in much the same way devoted parents have frequently distributed their special obligations across multiple children and across multiple parents. By taking up the extended analogy of parent we argue that doubly distributing special obligations need not contradict the possibility of special obligations in restructured collective forms of healthcare delivery and financing. (shrink)

A traditional ethic of medicine asserts that physicians have special obligations to individual patients with whom they have a clinical relationship. Contemporary trends in US healthcare financing like bundled payments seem to threaten traditional conceptions of special obligations of individual physicians to individual patients because their population-based focus sets a tone that seems to emphasise responsibilities for groups of patients by groups of physicians in an organisation. Prior to undertaking a cogent debate about the fate and normative weight of (...) special obligations and a traditional ethic for contemporary healthcare, we need a deeper examination of what the traditional ethic of special obligations really means. Here we offer a conception of ‘doubly distributed’ special obligations. Physicians and similarly minded healing professionals abiding by a traditional ethic have always spread their devotion and attention across multiple patients and have shared responsibilities with physician and non-physician colleagues in much the same way devoted parents have frequently distributed their special obligations across multiple children and across multiple parents. By taking up the extended analogy of parent we argue that doubly distributing special obligations need not contradict the possibility of special obligations in restructured collective forms of healthcare delivery and financing. (shrink)

Distributional semantic models (DSMs) are a primary method for distilling semantic information from corpora. However, a key question remains: What types of semantic relations among words do DSMs detect? Prior work typically has addressed this question using limited human data that are restricted to semantic similarity and/or general semantic relatedness. We tested eight DSMs that are popular in current cognitive and psycholinguistic research (positive pointwise mutual information; global vectors; and three variations each of Skip-gram and continuous bag of words (...) (CBOW) using word, context, and mean embeddings) on a theoretically motivated, rich set of semantic relations involving words from multiple syntactic classes and spanning the abstract–concrete continuum (19 sets of ratings). We found that, overall, the DSMs are best at capturing overall semantic similarity and also can capture verb–noun thematic role relations and noun–noun event-based relations that play important roles in sentence comprehension. Interestingly, Skip-gram and CBOW performed the best in terms of capturing similarity, whereas GloVe dominated the thematic role and event-based relations. We discuss the theoretical and practical implications of our results, make recommendations for users of these models, and demonstrate significant differences in model performance on event-based relations. (shrink)

I argue that information is a goal-relative concept for Bayesians. More precisely, I argue that how much information is provided by a piece of evidence depends on whether the goal is to learn the truth or to rank actions by their expected utility, and that different confirmation measures should therefore be used in different contexts. I then show how information measures may reasonably be derived from confirmation measures, and I show how to derive goal-relative non-informative and informative priors given background (...) information. Finally, I argue that my arguments have important implications for both objective and subjective Bayesianism. In particular, the Uniqueness Thesis is either false or must be modified. Moreover, objective Bayesians must concede that pragmatic factors systematically influence which priors are rational, and subjective Bayesians must concede that pragmatic factors sometimes partly determine which prior distribution most accurately represents an agent's epistemic state. (shrink)

When Bayesian estimation is used to analyze Structural Equation Models, prior distributions need to be specified for all parameters in the model. Many popular software programs offer default prior distributions, which is helpful for novel users and makes Bayesian SEM accessible for a broad audience. However, when the sample size is small, those prior distributions are not always suitable and can lead to untrustworthy results. In this tutorial, we provide a non-technical discussion of the risks associated with (...) the use of default priors in small sample contexts. We discuss how default priors can unintentionally behave as highly informative priors when samples are small. Also, we demonstrate an online educational Shiny app, in which users can explore the impact of varying prior distributions and sample sizes on model results. We discuss how the Shiny app can be used in teaching; provide a reading list with literature on how to specify suitable prior distributions; and discuss guidelines on how to recognize behaving priors. It is our hope that this tutorial helps to spread awareness of the importance of specifying suitable priors when Bayesian SEM is used with small samples. (shrink)

How is distributive justice possible with respect to immigration if political decisions about entry and membership cannot be grounded in the symmetry of a prior commonality, human or otherwise, that could guarantee reciprocal relations between members and nonmembers? This paper deals with both aspects of this question. Initially, it engages critically with Seyla Benhabib's plea for ‘dialogical universalism,’ showing why the strong discontinuity between political and moral reciprocity precludes understanding distributive justice as the process of mediating between political particularity (...) and moral universality. Subsequently, it suggests that a way out of this conceptual and normative impasse can be found in the fact that boundaries create a double asymmetry. This double asymmetry is constitutive for the ‘dia’ of the political dialogue that separates and joins members and nonmembers. This ‘in between,’ which eludes control by the parties to a dialogue, is the realm of distributive justice. (shrink)

Bose-Einstein statistics may be characterized in terms of multinomial distribution. From this characterization, an information theoretic analysis is made for Einstein-Podolsky-Rosen like situation; using Shannon’s measure of entropy.

In this paper I argue that individuals are, prior to the existence of just institutions requiring that they do so, bound as a matter of global distributive justice to restrict their use, or share the benefits fairly of any use beyond their entitlements, of the Earth’s capacity to absorb greenhouse gases (EAC) to within a specified justifiable range. As part of the search for an adequate account of climate morality, I approach the task by revisiting, and drawing inspiration from, (...) two prominent models from classical political philosophy for thinking about norms (rights, permissions, limits, etc.) regarding “pre-institutional” appropriation of unowned resources; Locke and Kant, respectively. The basic resources they develop—connected to fundamental norms of equality and rights to self-preservation and freedom—in order to generate their particular schema for distributive shares prior to the existence of just institutions can be usefully and plausibly connected up with the scarce, valuable, rival, non-excludable, global, and unowned resource that is EAC in order to undergird a picture of individual climate duties in the contemporary world. It is a picture that comes with some fairly radical implications, especially for the well-off. (shrink)

How is distributive justice possible with respect to immigration if political decisions about entry and membership cannot be grounded in the symmetry of a prior commonality, human or otherwise, that could guarantee reciprocal relations between members and nonmembers? This paper deals with both aspects of this question. Initially, it engages critically with Seyla Benhabib's plea for ‘dialogical universalism,’ showing why the strong discontinuity between political and moral reciprocity precludes understanding distributive justice as the process of mediating between political particularity (...) and moral universality. Subsequently, it suggests that a way out of this conceptual and normative impasse can be found in the fact that boundaries create a double asymmetry. This double asymmetry is constitutive for the ‘dia’ of the political dialogue that separates and joins members and nonmembers. This ‘in between,’ which eludes control by the parties to a dialogue, is the realm of distributive justice. (shrink)

The human ability to flexibly discover alternatives without fixating on a known solution supports a variety of human creative activities. Previous research has shown that people who discover an alternative procedure relax their attentional bias to information regarding the known solutions just prior to the discovery. This study examined whether the difference in the distribution of attention between the finders and non-finders of the alternative procedure is observed from the phase of solving the problem using the trained procedure. (...) We evaluated the characteristics of the finders' distribution of attention in situations where problem solving using a trained procedure was successful. This aspect has been little examined in previous research. Our study obtained empirical evidence for the fact that, compared to non-finders, finders pay more attention to information unrelated to the trained procedure acquired through knowledge and experience, even time when using a trained procedure. We also confirmed that this difference does not exist from the beginning of the task, but emerges during repeated use of familiar procedures. These findings indicate that in order to find an alternative procedure, one should not only divert attention from a familiar procedure just before the discovery but also pay a certain amount of attention to information unrelated to the familiar procedure even when the familiar procedure is functioning well. (shrink)

In a wide variety of contexts, individuals face a risk of being physically harmed by the conduct of others in the community. The extent to which the government protects individuals from such harmful behavior largely depends on the combined effect of administrative regulation, criminal law, and tort law. Unless these different departments are coordinated, the government cannot ensure that individuals are adequately secure from the cumulative threat of physical harm. What is adequate for this purpose depends on the underlying entitlement (...) to physical security. What one has lost for purposes of legal analysis depends on what one what was entitled to in the first instance. Consequently, any mode of safety regulation that requires an assessment of losses or costs ultimately depends on a prior specification of entitlements. For reasons of history and federalism, the entitlement in the United States can be derived from the common law of torts. In addition to establishing how costs should be measured, the tort entitlement also quantifies any distributive inequities that would be created by a safety standard and shows how they can be redressed within the safety regulation. When applied in this manner, the tort entitlement to physical security promotes substantive consistency across the different departments of law by serving as the distributive basis for environmental, health, and safety regulations that operate entirely outside of the tort system. (shrink)

John Rawls’ resistance to any kind of global egalitarian principle has seemed strange and unconvincing to many commentators, including those generally supportive of Rawls’ project. His rejection of a global egalitarian principle seems to rely on an assumption that states are economically bounded and separate from one another, which is not an accurate portrayal of economic relations among states in our globalised world. In this article, I examine the implications of the domestic theory of justice as fairness to argue that (...) Rawls has good reason to insist on economically bounded states. I argue that certain central features of the contemporary global economy, particularly the free movement of capital across borders, undermine the distributional autonomy required for states to realise Rawls’ principles of justice, and the domestic theory thus requires a certain degree of economic separation among states prior to the convening of the international original position. Given this, I defend Rawls’ reluctance to endorse a global egalitarian principle and defend a policy regime of international capital controls, to restore distributional autonomy and make the realisation of the principles of justice as fairness possible. (shrink)

Given someone’s fully specified posterior probability distribution q and information about the revision method that they employed to produce q, what can you infer about their prior probabilistic commitments? This question provides an entrée into a thoroughgoing discussion of a class of parameterizations of Jeffrey conditioning in which the parameters furnish information above and beyond that incorporated in \. Our analysis highlights the ubiquity of Bayes factors in the study of probability revision.

We investigate Maxwell's attempt to justify the mathematical assumptions behind his 1860 Proposition IV according to which the velocity components of colliding particles follow the normal distribution. Contrary to the commonly held view we find that his molecular collision model plays a crucial role in reaching this conclusion, and that his model assumptions also permit inference to equalization of mean kinetic energies, which is what he intended to prove in his discredited and widely ignored Proposition VI. If we take (...) a charitable reading of his own proof of Proposition VI then it was Maxwell, and not Boltzmann, who gave the first proof of a tendency towards equilibrium, a sort of H-theorem. We also call attention to a potential conflation of notions of probabilistic and value independence in relevant prior works of his contemporaries and of his own, and argue that this conflation might have impacted his adoption of the suspect independence assumption of Proposition IV. (shrink)

A new three-parameter extension of the generalized-exponential distribution, which has various hazard rates that can be increasing, decreasing, bathtub, or inverted tub, known as the Marshall-Olkin generalized-exponential distribution has been considered. So, this article addresses the problem of estimating the unknown parameters and survival characteristics of the three-parameter MOGE lifetime distribution when the sample is obtained from progressive type-II censoring via maximum likelihood and Bayesian approaches. Making use of the s-normality of classical estimators, two types of approximate (...) confidence intervals are constructed via the observed Fisher information matrix. Using gamma conjugate priors, the Bayes estimators against the squared-error and linear-exponential loss functions are derived. As expected, the Bayes estimates are not explicitly expressed, thus the Markov chain Monte Carlo techniques are implemented to approximate the Bayes point estimates and to construct the associated highest posterior density credible intervals. The performance of proposed estimators is evaluated via some numerical comparisons and some specific recommendations are also made. We further discuss the issue of determining the optimum progressive censoring plan among different competing censoring plans using three optimality criteria. Finally, two real-life datasets are analyzed to demonstrate how the proposed methods can be used in real-life scenarios. (shrink)

This paper explores the relation between perception, invizibilization and recognizability in the work of Rancière, Honneth and Butler. Recognizability is the term employed here to indicate the perceptual process that necessarily occurs prior to a normative or ethical act of recognition and that provides the conditions that make recognition possible. The notion of recognizability points to the fact that perception is not merely a disinterested surveying of the perceptual field but indicates that it is already evaluative in the sense (...) that others are immediately distinguishable from other objects. When a failure of recognizability occurs, it is not due to the fact that the other has not been seen in a literal sense but instead that she has been intentionally ignored or invisibilized. The suggestion made here is that despite their different approaches, a comparison and dialogue between these three thinkers highlights the importance of this constellation of issues for critical theory. (shrink)

Shortages of generic, injectable chemotherapeutics have been increasing in prevalence since 2006. Due to the lack of access to first-line, lifesaving treatments, physicians have been forced to ration chemotherapy between patients. Although the scarcity has been managed with good intentions, it has been done in an ad hoc manner, without the benefit of an ethically grounded and standardized schema. Using an approach based on the “accountability for reasonableness” method by Daniel and Sabin, I establish a framework and protocol for rationing (...) that is specific to chemotherapy. Prior to the state of true shortage, I present guidelines for the use of an adequate supply of chemotherapy with knowledge of upcoming scarcity. Within the rationing framework itself, I first prioritize emergency use of chemotherapeutics and those already receiving treatment at the time of shortage. I advocate for stratifying patients based on the prognostic indicators of their cancer type, using a combination of clinical-trial-based initial response and longer term survival, followed by the patients’ line of treatment. All patients who are not able to receive their “best” treatment must receive a sequent, next-best treatment, and their treatment team must have the ability to appeal to a rationing committee in special circumstances. I reject the ideas of stratification based on the intention of the treatment, perceived quality of life, pre-existing condition not impacting performance status, the classical “sickest first” argument, and giving preference to pediatric cases. Lastly, I advocate for any system of rationing to be transparent to those it affects and acknowledge the difficulties it presents to patients and physicians alike. (shrink)

In electrical resistance tomography technology for human lung, under the same experimental conditions, the width of the sensitive field boundary electrode has a significant impact on the calculation accuracy of the inverse problem besides the finite element model topology. Aiming to improve the quality of reconstructed images, the FEM for human lung was set up based on prior knowledge. On this basis, the electrode width of the FEM was optimised by comparing the morbidity degrees of the sensitivity matrix and (...) Hessian matrix, the uniformity of sensitivity distribution, and the quality of reconstructed images, which can improve the accuracy of solving the inverse problem significantly. (shrink)

Parametric cognitive models are increasingly popular tools for analyzing data obtained from psychological experiments. One of the main goals of such models is to formalize psychological theories using parameters that represent distinct psychological processes. We argue that systematic quantitative reviews of parameter estimates can make an important contribution to robust and cumulative cognitive modeling. Parameter reviews can benefit model development and model assessment by providing valuable information about the expected parameter space, and can facilitate the more efficient design of experiments. (...) Importantly, parameter reviews provide crucial—if not indispensable—information for the specification of informative prior distributions in Bayesian cognitive modeling. From the Bayesian perspective, prior distributions are an integral part of a model, reflecting cumulative theoretical knowledge about plausible values of the model's parameters (Lee,2018). In this paper we illustrate how systematic parameter reviews can be implemented to generate informed prior distributions for the Diffusion Decision Model (DDM; Ratcliff and McKoon,2008), the most widely used model of speeded decision making. We surveyed the published literature on empirical applications of the DDM, extracted the reported parameter estimates, and synthesized this information in the form of prior distributions. Our parameter review establishes a comprehensive reference resource for plausible DDM parameter values in various experimental paradigms that can guide future applications of the model. Based on the challenges we faced during the parameter review, we formulate a set of general and DDM-specific suggestions aiming to increase reproducibility and the information gained from the review process. (shrink)

Theories of truth approximation in terms of truthlikeness almost always deal with approaching deterministic truths, either actual or nomic. This paper deals first with approaching a probabilistic nomic truth, viz. a true probability distribution. It assumes a multinomial probabilistic context, hence with a lawlike true, but usually unknown, probability distribution. We will first show that this true multinomial distribution can be approached by Carnapian inductive probabilities. Next we will deal with the corresponding deterministic nomic truth, that is, (...) the set of conceptually possible outcomes with a positive true probability. We will introduce Hintikkian inductive probabilities, based on a prior distribution over the relevant deterministic nomic theories and on conditional Carnapian inductive probabilities, and first show that they enable again probabilistic approximation of the true distribution. Finally, we will show, in terms of a kind of success theorem, based on Niiniluoto’s estimated distance from the truth, in what sense Hintikkian inductive probabilities enable the probabilistic approximation of the relevant deterministic nomic truth. In sum, the truth approximation perspective on Carnapian and Hintikkian inductive probabilities leads to the unification of the inductive probability field and the field of truth approximation. (shrink)

The Gibbs sampler can be used to obtain samples of arbitrary size from the posterior distribution over the parameters of a structural equation model (SEM) given covariance data and a prior distribution over the parameters. Point estimates, standard deviations and interval estimates for the parameters can be computed from these samples. If the prior distribution over the parameters is uninformative, the posterior is proportional to the likelihood, and asymptotically the inferences based on the Gibbs sample (...) are the same as those based on the maximum likelihood solution, e.g., output from LISREL or EQS. In small samples, however, the likelihood surface is not Gaussian and in some cases contains local maxima. Nevertheless, the Gibbs sample comes from the correct posterior distribution over the parameters regardless of the sample size and the shape of the likelihood surface. With an informative prior distribution over the parameters, the posterior can be used to make inferences about the parameters of underidentified models, as we illustrate on a simple errors-in-variables model. (shrink)

Part I of the present work outlined the rigorous application of information theory to a quantum mechanical system in a thermodynamic equilibrium state. The general formula developed there for the best-guess density operator $\hat \rho$ was indeterminate because it involved in an essential way an unspecified prior probability distribution over the continuumD H of strong equilibrium density operators. In Part II mathematical evaluation of $\hat \rho$ is completed after an epistemological analysis which leads first to the discretization ofD (...) H and then to the adoption of a suitable indifference axiom to delimit the set of admissible prior distributions. Finally, quantal formulas for information-theoretic and thermodynamic entropies are contrasted, and the entire work is summarized. (shrink)

A decision maker bets on the outcomes of a sequence of coin-tossings. At the beginning of the game the decision maker can choose one of two coins to play the game. This initial choice is irreversible. The coins can be biased and the player is uncertain about the nature of one (or possibly both) coin(s). If the player is an expected-utility maximizer, her choice of the coin will depend on different elements: the nature of the game (namely, whether she can (...) observe the outcomes of the previous tosses before making her next decision), her utility function, the prior distribution on the bias of the coin. We will show that even a risk averter might optimally choose a riskier coin when learning is allowed. We will express most of our results in the language of stochastic orderings, allowing comparisons that are valid for large classes of utility functions. (shrink)