Este escrito surge de nuestras investigaciones sobre la caracterización y las fuentes del republicanismo arendtiano y pretende intervenir en el debate urgente que se abre acerca de nuestras democracias contemporáneas. Es en este panorama que quisiéramos ubicar nuestras reflexiones con la expectativa de reintroducir, a través del pensamiento de Hannah Arendt, ciertos aspectos que consideramos centrales para pensar la república y que han sido dejados de lado en el debate público sobre los regímenes políticos contemporáneos. Estos son el lugar del (...) pueblo en la república, su función y su dinámica política en la vida de las instituciones y en la expresión de la libertad en el orden político contemporáneo. En efecto, sostendremos en este trabajo que las reflexiones de Arendt sobre la república están íntimamente ligadas a la figura, o, deberíamos decir mejor, a las múltiples figuras del pueblo y al rol que ellas juegan en la institución política de la libertad. (shrink)

The tendency to test outcomes that are predicted by our current theory (the confirmation bias) is one of the best-known biases of human decision making. We prove that the confirmation bias is an optimal strategy for testing hypotheses when those hypotheses are deterministic, each making a single prediction about the next event in a sequence. Our proof applies for two normative standards commonly used for evaluating hypothesis testing: maximizing expected information gain and maximizing the probability of falsifying the current hypothesis. (...) This analysis rests on two assumptions: (a) that people predict the next event in a sequence in a way that is consistent with Bayesian inference; and (b) when testing hypotheses, people test the hypothesis to which they assign highest posterior probability. We present four behavioral experiments that support these assumptions, showing that a simple Bayesian model can capture people's predictions about numerical sequences (Experiments 1 and 2), and that we can alter the hypotheses that people choose to test by manipulating the prior probability of those hypotheses (Experiments 3 and 4). (shrink)

Popular press headlines frequently reveal unethical or illegal activity in business and sports. Given these parallel ethical lapses in business and sport, our study examines potential relationships between student sport involvement (active and passive) and ethical judgments regarding issues in sport and business. Our results, based on a sample of 202 undergraduates in an upper-division management class, indicate a significant negative relationship between high passive sport involvement and ethical judgments about sport issues as well as a consistent significant positive relationship (...) between female gender and ethical judgments about sport and business issues. (shrink)

Sheryl Swoopes is an African American woman and a celebrity in the US Women’s National Basketball Association. In 2005, she announced she was in a seven-year relationship with a woman and received a six figure endorsement deal with a lesbian cruise line. Swoopes was also branded as a mother and married to a man — inferring heterosexuality. The article uses the ‘coming out’ to look at the interconnections of race, gender, class, sexual orientation, and celebrity identities. Using discourse analysis the (...) article examines both academic and popular discourse to raise the question: ‘Is Sheryl Swoopes a lesbian?’ When can she self-identify as a lesbian and become an insider in the queer community? The article argues for feminists to see oppressions as multiplicative, rather than using the adding-on approach. Identifying celebrity as a capitalist identity, the article shows the challenges of identity and discourse and how they continue to frame our theological method. (shrink)

Recent events at Enron, K-Mart, Adelphia, and Tyson would seem to suggest that managers are still experiencing ethical lapses. These lapses are somewhat surprising and disappointing given the heightened focus on ethical considerations within business contexts during the past decade. This study is designed, therefore, to increase our understanding of the forces that shape ethical perceptions by considering the effects of business school education as well as a number of other individual-level factors (such as intra-national culture, area of specialization within (...) business, and gender) that may exert an influence on ethical perceptions. We found significant effects for business education, self-reported intra-national culture, area of specialization within business, and gender for some and/or all areas of ethics examined (i.e., deceit, fraud, self-interest, influence dealing, and coercion). One of our most encouraging findings is that tolerance for unethical behavior appears to decrease with formal business education. Despite the prevalent stereotype that business students are only interested in the bottom line or that business schools transform idealistic freshman into self-serving business graduates, our results suggest otherwise. Given the heightened criticism of the ethicality of contemporary managerial behavior, it is heartening to note that, even as adults, individuals can be positively affected by integration of ethics training. (shrink)

How does the visual system recognize images of a novel object after a single observation despite possible variations in the viewpoint of that object relative to the observer? One possibility is comparing the image with a prototype for invariance over a relevant transformation set. However, invariance over rotations has proven difficult to analyze, because it applies to some objects but not others. We propose that the invariant transformations of an object are learned by incorporating prior expectations with real-world evidence. We (...) test this proposal by developing an ideal learner model for learning invariance that predicts better learning of orientation dependence when prior expectations about orientation are weak. This prediction was supported in two behavioral experiments, where participants learned the orientation dependence of novel images using feedback from solving arithmetic problems. (shrink)

This study of 481 corporations provides an assessment of the relationship between several corporate governance variables (board composition, type of board leadership, officer and director stock holdings, institutional stock holdings, number of majority owners, existence of severance agreements) and adoption of anti-takeover amendments. The results of analysis suggest that the two groups (adopters/non-adopters) differ significantly in regards to these variables.

This study of major corporations (n=481) provides an empirical assessment of the effects of several corporate governance variables (CEO duality, boards of director composition, officers and directors common stock holdings, institutional common stock holdings, number of majority owners) on the adoption of so-called severance agreements. A discriminant analysis indicates a significant multivariate function. Wilks lambda univariate analyses suggest that the percentage of common stock held by owners and directors and number of majority stock holders are the more robust discriminators.

The implementation of new methods of treating and preventing disease raises many question of both technical and moral character. Currently, many studies focus on developing a screening test for preeclampsia (PE), a disease complicating 2–8% of pregnancies, potentially causing severe consequences for pregnant women and their fetuses. The purpose is to develop a test that can identify pregnancies at high risk for developing PE sufficiently early in pregnancy to allow for prophylaxis. However, the question of implementing a screening test for (...) PE does not only involve an evaluation of technical feasibility and clinical efficacy, it also requires an analysis of how the test influences the conditions and choices for those tested. This study evaluates state-of-the-art techniques for preeclampsia screening in an ethical framework, pointing out the central areas of moral relevance within the context of such screening activity. Furthermore, we propose ethical guidelines that a screening programme for PE should meet in order to become an uncontroversial addition to prenatal health care. (shrink)

Before September 11, 2001, a mass-casualty terrorist attack on American soil was generally considered a remote possibility. Similarly, before October 4, 2001—the first confirmed case of anthrax caused by intentional release — widespread bioterrorism seemed implausible. Among the arguments that such a biological artack was unlikely included: the lack of a historical precedent; the technological and organizational challenges to acquiring and weaponizing a biological agent; and the almost universal moral opprobrium that would certainly accompany the use by terrorists of such (...) a weapon. In the wake of September 11th and October 4th, however, many are reconsidering the likelihood of a large-scale bioterrorist attack against civilians.The Centers for Disease Control and Prevention defines bioterrorism as the intentional release of viruses, bacteria, or toxins for the purpose of harming or killing civilian. One measurement of the public health system's level of bioterrorism preparedness is the quality and distribution of laws mandating the reporting of diseases caused by certain biological agents. (shrink)

Before September 11, 2001, a mass-casualty terrorist attack on American soil was generally considered a remote possibility. Similarly, before October 4, 2001—the first confirmed case of anthrax caused by intentional release — widespread bioterrorism seemed implausible. Among the arguments that such a biological artack was unlikely included: the lack of a historical precedent; the technological and organizational challenges to acquiring and weaponizing a biological agent; and the almost universal moral opprobrium that would certainly accompany the use by terrorists of such (...) a weapon. In the wake of September 11th and October 4th, however, many are reconsidering the likelihood of a large-scale bioterrorist attack against civilians.The Centers for Disease Control and Prevention defines bioterrorism as the intentional release of viruses, bacteria, or toxins for the purpose of harming or killing civilian. One measurement of the public health system's level of bioterrorism preparedness is the quality and distribution of laws mandating the reporting of diseases caused by certain biological agents. (shrink)

Antonio Gramsci is one of the major social and political theorists of the 20th century whose work has had an enormous influence on several fields, including educational theory and practice. Gramsci and Education demonstrates the relevance of Antonio Gramsci's thought for contemporary educational debates. The essays are written by scholars located in different parts of the world, a number of whom are well known internationally for their contributions to Gramscian scholarship and/or educational research. The collection deals with a broad range (...) of topics, including schooling, adult education in general, popular education, workers' education, cultural studies, critical pedagogy, multicultural education, and the role of intellectuals in contemporary society. (shrink)

The purpose of this paper is to present the theoretical and philosophical assumptions of the Nursing Manifesto , written by three activist scholars whose objective was to promote emancipatory nursing research, practice, and education within the dialogue and praxis of social justice. Inspired by discussions with a number of nurse philosophers at the 2008 Knowledge Conference in Boston, two of the original Manifesto authors and two colleagues discussed the need to explicate emancipatory knowing as it emerged from the Manifesto . (...) Our analysis yielded an epistemological framework based on liberation principles to advance praxis in the discipline of nursing. This paper adds to what is already known on this topic, as there is not an explicit contribution to the literature of this specific Manifesto , its significance, and utility for the discipline. While each of us have written on emancipatory knowing and social justice in a variety of works, it is in this article that we identify, as a unit of knowledge production and as a direction towards praxis, a set of critical values that arose from the emancipatory conscience-ness and intention seen in the framework of the Nursing Manifesto. (shrink)

The purpose of this paper is to present the theoretical and philosophical assumptions of the Nursing Manifesto, written by three activist scholars whose objective was to promote emancipatory nursing research, practice, and education within the dialogue and praxis of social justice. Inspired by discussions with a number of nurse philosophers at the 2008 Knowledge Conference in Boston, two of the original Manifesto authors and two colleagues discussed the need to explicate emancipatory knowing as it emerged from the Manifesto. Our analysis (...) yielded an epistemological framework based on liberation principles to advance praxis in the discipline of nursing. This paper adds to what is already known on this topic, as there is not an explicit contribution to the literature of this specific Manifesto, its significance, and utility for the discipline. While each of us have written on emancipatory knowing and social justice in a variety of works, it is in this article that we identify, as a unit of knowledge production and as a direction towards praxis, a set of critical values that arose from the emancipatory conscience-ness and intention seen in the framework of the Nursing Manifesto. (shrink)

Can sentence comprehension impairments in aphasia be explained by difficulties arising from dependency completion processes in parsing? Two distinct models of dependency completion difficulty are investigated, the Lewis and Vasishth (2005) activation-based model and the direct-access model (DA; McElree, 2000). These models' predictive performance is compared using data from individuals with aphasia (IWAs) and control participants. The data are from a self-paced listening task involving subject and object relative clauses. The relative predictive performance of the models is evaluated using k-fold (...) cross-validation. For both IWAs and controls, the activation-based model furnishes a somewhat better quantitative fit to the data than the DA. Model comparisons using Bayes factors show that, assuming an activation-based model, intermittent deficiencies may be the best explanation for the cause of impairments in IWAs, although slowed syntax and lexical delayed access may also play a role. This is the first computational evaluation of different models of dependency completion using data from impaired and unimpaired individuals. This evaluation develops a systematic approach that can be used to quantitatively compare the predictions of competing models of language processing. (shrink)

Can sentence comprehension impairments in aphasia be explained by difficulties arising from dependency completion processes in parsing? Two distinct models of dependency completion difficulty are investigated, the Lewis and Vasishth (2005) activation‐based model and the direct‐access model (DA; McElree, 2000). These models' predictive performance is compared using data from individuals with aphasia (IWAs) and control participants. The data are from a self‐paced listening task involving subject and object relative clauses. The relative predictive performance of the models is evaluated using k‐fold (...) cross‐validation. For both IWAs and controls, the activation‐based model furnishes a somewhat better quantitative fit to the data than the DA. Model comparisons using Bayes factors show that, assuming an activation‐based model, intermittent deficiencies may be the best explanation for the cause of impairments in IWAs, although slowed syntax and lexical delayed access may also play a role. This is the first computational evaluation of different models of dependency completion using data from impaired and unimpaired individuals. This evaluation develops a systematic approach that can be used to quantitatively compare the predictions of competing models of language processing. (shrink)

In many learning or inference tasks human behavior approximates that of a Bayesian ideal observer, suggesting that, at some level, cognition can be described as Bayesian inference. However, a number of findings have highlighted an intriguing mismatch between human behavior and standard assumptions about optimality: People often appear to make decisions based on just one or a few samples from the appropriate posterior probability distribution, rather than using the full distribution. Although sampling-based approximations are a common way to implement Bayesian (...) inference, the very limited numbers of samples often used by humans seem insufficient to approximate the required probability distributions very accurately. Here, we consider this discrepancy in the broader framework of statistical decision theory, and ask: If people are making decisions based on samples—but as samples are costly—how many samples should people use to optimize their total expected or worst-case reward over a large number of decisions? We find that under reasonable assumptions about the time costs of sampling, making many quick but locally suboptimal decisions based on very few samples may be the globally optimal strategy over long periods. These results help to reconcile a large body of work showing sampling-based or probability matching behavior with the hypothesis that human cognition can be understood in Bayesian terms, and they suggest promising future directions for studies of resource-constrained cognition. (shrink)

Shepard has argued that a universal law should govern generalization across different domains of perception and cognition, as well as across organisms from different species or even different planets. Starting with some basic assumptions about natural kinds, he derived an exponential decay function as the form of the universal generalization gradient, which accords strikingly well with a wide range of empirical data. However, his original formulation applied only to the ideal case of generalization from a single encountered stimulus to a (...) single novel stimulus, and for stimuli that can be represented as points in a continuous metric psychological space. Here we recast Shepard's theory in a more general Bayesian framework and show how this naturally extends his approach to the more realistic situation of generalizing from multiple consequential stimuli with arbitrary representational structure. Our framework also subsumes a version of Tversky's set-theoretic model of similarity, which is conventionally thought of as the primary alternative to Shepard's continuous metric space model of similarity and generalization. This unification allows us not only to draw deep parallels between the set-theoretic and spatial approaches, but also to significantly advance the explanatory power of set-theoretic models. Key Words: additive clustering; Bayesian inference; categorization; concept learning; contrast model; features; generalization; psychological space; similarity. (shrink)

In this book chapter, Moya argues that recognizing, indeed mobilizing, identities in the classroom is a necessary part of educating for a just and democratic society. Only a truly multi-perspectival, multicultural education can create the conditions needed to alter the negative identity contingencies that minority students commonly face, while creating opportunities for all students. By treating identities as epistemic resources and mobilizing them, we can draw out their knowledge-generating potential and allow them to contribute positively to the production and transmission (...) of knowledge. (shrink)

Analyzing the rate at which languages change can clarify whether similarities across languages are solely the result of cognitive biases or might be partially due to descent from a common ancestor. To demonstrate this approach, we use a simple model of language evolution to mathematically determine how long it should take for the distribution over languages to lose the influence of a common ancestor and converge to a form that is determined by constraints on language learning. We show that modeling (...) language learning as Bayesian inference of n binary parameters or the ordering of n constraints results in convergence in a number of generations that is on the order of n log n. We relax some of the simplifying assumptions of this model to explore how different assumptions about language evolution affect predictions about the time to convergence; in general, convergence time increases as the model becomes more realistic. This allows us to characterize the assumptions about language learning (given the models that we consider) that are sufficient for convergence to have taken place on a timescale that is consistent with the origin of human languages. These results clearly identify the consequences of a set of simple models of language evolution and show how analysis of convergence rates provides a tool that can be used to explore questions about the relationship between accounts of language learning and the origins of similarities across languages. (shrink)

Language research has come to rely heavily on large‐scale, web‐based datasets. These datasets can present significant methodological challenges, requiring researchers to make a number of decisions about how they are collected, represented, and analyzed. These decisions often concern long‐standing challenges in corpus‐based language research, including determining what counts as a word, deciding which words should be analyzed, and matching sets of words across languages. We illustrate these challenges by revisiting “Word lengths are optimized for efficient communication” (Piantadosi, Tily, & Gibson, (...) 2011), which found that word lengths in 11 languages are more strongly correlated with their average predictability (or average information content) than their frequency. Using what we argue to be best practices for large‐scale corpus analyses, we find significantly attenuated support for this result and demonstrate that a stronger relationship obtains between word frequency and length for a majority of the languages in the sample. We consider the implications of the results for language research more broadly and provide several recommendations to researchers regarding best practices. (shrink)

Generalization is a fundamental problem solved by every cognitive system in essentially every domain. Although it is known that how people generalize varies in complex ways depending on the context or domain, it is an open question how people learn the appropriate way to generalize for a new context. To understand this capability, we cast the problem of learning how to generalize as a problem of learning the appropriate hypothesis space for generalization. We propose a normative mathematical framework for learning (...) how to generalize by learning inductive biases for which properties are relevant for generalization in a domain from the statistical structure of features and concepts observed in that domain. More formally, the framework predicts that an ideal learner should learn to generalize by either taking the weighted average of the results of generalizing according to each hypothesis space, with weights given by how well each hypothesis space fits the previously observed concepts, or by using the most likely hypothesis space. We compare the predictions of this framework to human generalization behavior with three experiments in one perceptual (rectangles) and two conceptual (animals and numbers) domains. Across all three studies we find support for the framework's predictions, including individual‐level support for averaging in the third study. (shrink)

Current psychological theories of human causal learning and judgment focus primarily on long-run predictions: two by estimating parameters of a causal Bayes nets, and a third through structural learning. This paper focuses on people’s short-run behavior by examining dynamical versions of these three theories, and comparing their predictions to a real-world dataset.

Marr's levels of analysis—computational, algorithmic, and implementation—have served cognitive science well over the last 30 years. But the recent increase in the popularity of the computational level raises a new challenge: How do we begin to relate models at different levels of analysis? We propose that it is possible to define levels of analysis that lie between the computational and the algorithmic, providing a way to build a bridge between computational- and algorithmic-level models. The key idea is to push the (...) notion of rationality, often used in defining computational-level models, deeper toward the algorithmic level. We offer a simple recipe for reverse-engineering the mind's cognitive strategies by deriving optimal algorithms for a series of increasingly more realistic abstract computational architectures, which we call “resource-rational analysis.”. (shrink)