Results for 'Joshua B. Hardin'

972 found
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  1.  16
    Giving nurses a voice during ethical conflict in the Intensive Care Unit.Natalie S. McAndrew & Joshua B. Hardin - 2020 - Nursing Ethics 27 (8):1631-1644.
    Background: Ethical conflict and subsequent nurse moral distress and burnout are common in the intensive care unit (ICU). There is a gap in our understanding of nurses’ perceptions of how organizational resources support them in addressing ethical conflict in the intensive care unit. Research question/objectives/methods: The aim of this qualitative, descriptive study was to explore how nurses experience ethical conflict and use organizational resources to support them as they address ethical conflict in their practice. Participants and research context: Responses to (...)
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  2. Generalization, similarity, and bayesian inference.Joshua B. Tenenbaum & Thomas L. Griffiths - 2001 - Behavioral and Brain Sciences 24 (4):629-640.
    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 (...)
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  3.  56
    Intuitive theories as grammars for causal inference.Joshua B. Tenenbaum, Thomas L. Griffiths & Sourabh Niyogi - 2007 - In Alison Gopnik & Laura Schulz (eds.), Causal learning: psychology, philosophy, and computation. New York: Oxford University Press. pp. 301--322.
  4. Defending Opioid Treatment Agreements: Disclosure, Not Promises.Joshua B. Rager & Peter H. Schwartz - 2017 - Hastings Center Report 47 (3):24-33.
    In order to receive controlled pain medications for chronic non-oncologic pain, patients often must sign a “narcotic contract” or “opioid treatment agreement” in which they promise not to give pills to others, use illegal drugs, or seek controlled medications from health care providers. In addition, they must agree to use the medication as prescribed and to come to the clinic for drug testing and pill counts. Patients acknowledge that if they violate the opioid treatment agreement, they may no longer receive (...)
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  5.  24
    Some specifics about generalization.Joshua B. Tenenbaum & Thomas L. Griffiths - 2001 - Behavioral and Brain Sciences 24 (4):762-778.
  6.  34
    Practicing Novel, Praxis-Like Movements: Physiological Effects of Repetition.Joshua B. Ewen, Ajay S. Pillai, Danielle McAuliffe, Balaji M. Lakshmanan, Katarina Ament, Mark Hallett, Nathan E. Crone & Stewart H. Mostofsky - 2016 - Frontiers in Human Neuroscience 10:171622.
    Our primary goal was to develop and validate a task that could provide evidence about how humans learn praxis gestures, such as those involving the use of tools. To that end, we created a video-based task in which subjects view a model performing novel, meaningless one-handed actions with kinematics similar to praxis gestures. Subjects then imitated the movements with their right hand. Trials were repeated 6 times to examine practice effects. EEG was recorded during the task. As a control, subjects (...)
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  7.  52
    Inferring causal networks from observations and interventions.Mark Steyvers, Joshua B. Tenenbaum, Eric-Jan Wagenmakers & Ben Blum - 2003 - Cognitive Science 27 (3):453-489.
    Information about the structure of a causal system can come in the form of observational data—random samples of the system's autonomous behavior—or interventional data—samples conditioned on the particular values of one or more variables that have been experimentally manipulated. Here we study people's ability to infer causal structure from both observation and intervention, and to choose informative interventions on the basis of observational data. In three causal inference tasks, participants were to some degree capable of distinguishing between competing causal hypotheses (...)
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  8.  18
    Cynthia R. Nielsen, Foucault, Douglass, Fanon, and Scotus in Dialogue: On Social Construction and Freedom.Joshua B. Cutts - 2015 - Foucault Studies 19:229-233.
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  9.  82
    M-Zeroids: Structure and Categorical Equivalence.Joshua B. Palmatier & Fernando Guzman - 2012 - Studia Logica 100 (5):975-1000.
    In this note we develop a method for constructing finite totally-ordered m-zeroids and prove that there exists a categorical equivalence between the category of finite, totally-ordered m-zeroids and the category of pseudo Łukasiewicz-like implicators.
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  10. Theory-based Bayesian models of inductive learning and reasoning.Joshua B. Tenenbaum, Thomas L. Griffiths & Charles Kemp - 2006 - Trends in Cognitive Sciences 10 (7):309-318.
  11.  13
    The cost of crisis in clinical psychological science.Joshua B. Grubbs - 2022 - Behavioral and Brain Sciences 45.
    Yarkoni has argued that psychology is facing a generalizability crisis, but the real cost of this crisis is obscured by a focus on topics from psychology's most academic subfields. Psychology is also filled with applied subfields, and it is within those subfields – especially clinical science – where the cost of a generalizability crisis will be most severe.
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  12.  13
    Mediation Training for the Physician: Expanding the Communication Toolkit to Manage Conflict.Joshua B. Kayser - 2015 - Journal of Clinical Ethics 26 (4):339-341.
    Good communication is critical to the practice of medicine. This is particularly true when outcomes are unpredictable and/or patients lack the capacity to participate in medical decision making. Disputes may develop that cannot be addressed using basic communication skills. Conflict of this nature can burden patients, families, and medical staff and may result in increased suffering for all parties. Many physicians lack the necessary communication tools to handle difficult conversations. Training in bioethics mediation provides physicians with skills that can promote (...)
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  13.  11
    Democratic Experimentation with Responsibility: A Pragmatist Approach to Responsible Research and Innovation.Joshua B. Cohen & Robert Gianni - 2022 - In Vincent Blok (ed.), Putting Responsible Research and Innovation into Practice: A Multi-Stakeholder Approach. dordrecht: springer. pp. 57-77.
    Disruptive societal changes following from emerging science and technology have recently led to a growing interest in developing ethical frameworks. Responsible Research and Innovation (RRI) is such a framework that aims to improve the relationship between science and society. Now a decade after its conceptualization, it still seems to suffer from conceptual unclarity and lack of implementation. Since responsibility in research and innovation practice remains as important as ever, we propose to revive the normative potential of RRI by approaching it (...)
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  14.  77
    Probabilistic models of cognition: where next?Nick Chater, Joshua B. Tenenbaum & Alan Yuille - 2006 - Trends in Cognitive Sciences 10 (7):292-293.
  15.  40
    Decreased Modulation of EEG Oscillations in High-Functioning Autism during a Motor Control Task.Joshua B. Ewen, Balaji M. Lakshmanan, Ajay S. Pillai, Danielle McAuliffe, Carrie Nettles, Mark Hallett, Nathan E. Crone & Stewart H. Mostofsky - 2016 - Frontiers in Human Neuroscience 10:187244.
    Autism spectrum disorders (ASD) are thought to result in part from altered cortical excitatory-inhibitory balance; this pathophysiology may impact the generation of oscillations on EEG. We investigated premotor-parietal cortical physiology associated with praxis, which has strong theoretical and empirical associations with ASD symptomatology. 25 children with high-functioning ASD (HFA) and 33 controls performed a praxis task involving the pantomiming of tool use, while EEG was recorded. We assessed task-related modulation of signal power in alpha and beta frequency bands. Compared with (...)
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  16.  87
    Bootstrapping in a language of thought: A formal model of numerical concept learning.Steven T. Piantadosi, Joshua B. Tenenbaum & Noah D. Goodman - 2012 - Cognition 123 (2):199-217.
  17. Moral Grandstanding in Public Discourse: Status-Seeking Motives as a Potential Explanatory Mechanism in Predicting Conflict.Joshua B. Grubbs, Brandon Warmke, Justin Tosi, A. Shanti James & W. Keith Campbell - 2019 - PLoS ONE 14 (10).
    Public discourse is often caustic and conflict-filled. This trend seems to be particularly evident when the content of such discourse is around moral issues (broadly defined) and when the discourse occurs on social media. Several explanatory mechanisms for such conflict have been explored in recent psychological and social-science literatures. The present work sought to examine a potentially novel explanatory mechanism defined in philosophical literature: Moral Grandstanding. According to philosophical accounts, Moral Grandstanding is the use of moral talk to seek social (...)
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  18. Moral grandstanding and political polarization: A multi-study consideration.Joshua B. Grubbs, Brandon Warmke, Justin Tosi & A. Shanti James - 2020 - Journal of Research in Personality 88.
    The present work posits that social motives, particularly status seeking in the form of moral grandstanding, are likely at least partially to blame for elevated levels of affective polarization and ideological extremism in the U.S. In Study 1, results from both undergraduates (N = 981; Mean age = 19.4; SD = 2.1; 69.7% women) and a cross-section of U.S. adults matched to 2010 census norms (N = 1,063; Mean age = 48.20, SD = 16.38; 49.8% women) indicated that prestige-motived grandstanding (...)
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  19.  34
    Theory-based causal induction.Thomas L. Griffiths & Joshua B. Tenenbaum - 2009 - Psychological Review 116 (4):661-716.
  20.  63
    Sleep Deprivation and Sustained Attention Performance: Integrating Mathematical and Cognitive Modeling.Glenn Gunzelmann, Joshua B. Gross, Kevin A. Gluck & David F. Dinges - 2009 - Cognitive Science 33 (5):880-910.
    A long history of research has revealed many neurophysiological changes and concomitant behavioral impacts of sleep deprivation, sleep restriction, and circadian rhythms. Little research, however, has been conducted in the area of computational cognitive modeling to understand the information processing mechanisms through which neurobehavioral factors operate to produce degradations in human performance. Our approach to understanding this relationship is to link predictions of overall cognitive functioning, or alertness, from existing biomathematical models to information processing parameters in a cognitive architecture, leveraging (...)
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  21.  51
    From mere coincidences to meaningful discoveries.Thomas L. Griffiths & Joshua B. Tenenbaum - 2007 - Cognition 103 (2):180-226.
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  22.  81
    A critical period for second language acquisition: Evidence from 2/3 million English speakers.Joshua K. Hartshorne, Joshua B. Tenenbaum & Steven Pinker - 2018 - Cognition 177 (C):263-277.
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  23.  36
    Structured statistical models of inductive reasoning.Charles Kemp & Joshua B. Tenenbaum - 2009 - Psychological Review 116 (1):20-58.
  24.  17
    Randomness and Coincidences: Reconciling Intuition and Probability Theory.Thomas L. Griffiths & Joshua B. Tenenbaum - unknown
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  25.  65
    The logical primitives of thought: Empirical foundations for compositional cognitive models.Steven T. Piantadosi, Joshua B. Tenenbaum & Noah D. Goodman - 2016 - Psychological Review 123 (4):392-424.
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  26.  76
    Three ideal observer models for rule learning in simple languages.Michael C. Frank & Joshua B. Tenenbaum - 2011 - Cognition 120 (3):360-371.
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  27.  36
    Dissociating intuitive physics from intuitive psychology: Evidence from Williams syndrome.Frederik S. Kamps, Joshua B. Julian, Peter Battaglia, Barbara Landau, Nancy Kanwisher & Daniel D. Dilks - 2017 - Cognition 168 (C):146-153.
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  28.  60
    Rational statistical inference: A critical component for word learning.Fei Xu & Joshua B. Tenenbaum - 2001 - Behavioral and Brain Sciences 24 (6):1123-1124.
    In order to account for how children can generalize words beyond a very limited set of labeled examples, Bloom's proposal of word learning requires two extensions: a better understanding of the “general learning and memory abilities” involved, and a principled framework for integrating multiple conflicting constraints on word meaning. We propose a framework based on Bayesian statistical inference that meets both of those needs.
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  29. Beyond Boolean logic: exploring representation languages for learning complex concepts.Steven T. Piantadosi, Joshua B. Tenenbaum & Noah D. Goodman - 2010 - In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 859--864.
  30.  12
    Misrecognitions: Gillian Rose and the task of political theology.Joshua B. Davis (ed.) - 2018 - Eugene, Oregon,: Cascade Books.
    This collection brings together prominent thinkers from numerous disciplines to address the legacy of Gillian Rose for political theology today. Rose’s work is notorious for its eclectic range, difficult style, and iconoclastic defiance of the conventions of postmodern critical theory. The theologians, religious scholars, ethicists, and theorists in this collection discuss Rose’s relationship to such topics as the Frankfurt School, social theory, feminism, literature, law, Hegel, Kant, and psychoanalysis. They situate her work within the wider context of political theology, as (...)
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  31.  96
    Word learning as Bayesian inference.Fei Xu & Joshua B. Tenenbaum - 2007 - Psychological Review 114 (2):245-272.
  32.  47
    Two proposals for causal grammars.Thomas L. Griffiths & Joshua B. Tenenbaum - 2007 - In Alison Gopnik & Laura Schulz (eds.), Causal learning: psychology, philosophy, and computation. New York: Oxford University Press. pp. 323--345.
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  33.  46
    Encoding higher-order structure in visual working memory: A probabilistic model.Timothy F. Brady & Joshua B. Tenenbaum - 2010 - In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 411--416.
  34.  24
    Corrigendum to “Three ideal observer models for rule learning in simple languages” [Cognition 120 (3) (2011) 360–371].Michael C. Frank & Joshua B. Tenenbaum - 2014 - Cognition 132 (3):501.
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  35.  21
    “Structured statistical models of inductive reasoning”: Correction.Charles Kemp & Joshua B. Tenenbaum - 2009 - Psychological Review 116 (2):461-461.
  36. Moral grandstanding, narcissism, and self-reported responses to the COVID-19 crisis.Joshua B. Grubbs, A. Shanti James, Brandon Warmke & Justin Tosi - 2022 - Journal of Research in Personality 97 (104187):1-10.
    The present study aimed to understand how status-oriented individual differences such as narcissistic antagonism, narcissistic extraversion, and moral grandstanding motivations may have longitudinally predicted both behavioral and social media responses during the early stages of the COVID-19 pandemic. Via YouGov, a nationally representative sample of U.S. adults was recruited in August of 2019 (N = 2,519; Mage = 47.5, SD = 17.8; 51.4% women) and resampled in May of 2020, (N = 1,533). Results indicated that baseline levels of narcissistic antagonism (...)
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  37.  25
    A probabilistic model of visual working memory: Incorporating higher order regularities into working memory capacity estimates.Timothy F. Brady & Joshua B. Tenenbaum - 2013 - Psychological Review 120 (1):85-109.
  38.  46
    Visual attention to features by associative learning.Davood G. Gozli, Joshua B. Moskowitz & Jay Pratt - 2014 - Cognition 133 (2):488-501.
  39. A tutorial introduction to Bayesian models of cognitive development.Amy Perfors, Joshua B. Tenenbaum, Thomas L. Griffiths & Fei Xu - 2011 - Cognition 120 (3):302-321.
  40.  12
    Cytoskeletal diversification across 1 billion years: What red algae can teach us about the cytoskeleton, and vice versa.Holly V. Goodson, Joshua B. Kelley & Susan H. Brawley - 2021 - Bioessays 43 (5):2000278.
    The cytoskeleton has a central role in eukaryotic biology, enabling cells to organize internally, polarize, and translocate. Studying cytoskeletal machinery across the tree of life can identify common elements, illuminate fundamental mechanisms, and provide insight into processes specific to less‐characterized organisms. Red algae represent an ancient lineage that is diverse, ecologically significant, and biomedically relevant. Recent genomic analysis shows that red algae have a surprising paucity of cytoskeletal elements, particularly molecular motors. Here, we review the genomic and cell biological evidence (...)
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  41.  76
    Concepts are not beliefs, but having concepts is having beliefs.Fei Xu, Joshua B. Tenenbaum & Cristina M. Sorrentino - 1998 - Behavioral and Brain Sciences 21 (1):89-89.
    We applaud Millikan's psychologically plausible version of the causal theory of reference. Her proposal offers a significant clarification of the much-debated relation between concepts and beliefs, and suggests positive directions for future empirical studies of conceptual development. However, Millikan's revision of the causal theory may leave us with no generally satisfying account of concept individuation in the mind.
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  42.  98
    The Large‐Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic Growth.Mark Steyvers & Joshua B. Tenenbaum - 2005 - Cognitive Science 29 (1):41-78.
    We present statistical analyses of the large‐scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small‐world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of connections follow power laws that indicate a scale‐free pattern of connectivity, with most nodes having relatively few connections joined together through a small number of hubs with many connections. These regularities (...)
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  43.  62
    The learnability of abstract syntactic principles.Amy Perfors, Joshua B. Tenenbaum & Terry Regier - 2011 - Cognition 118 (3):306-338.
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  44.  19
    A theory of learning to infer.Ishita Dasgupta, Eric Schulz, Joshua B. Tenenbaum & Samuel J. Gershman - 2020 - Psychological Review 127 (3):412-441.
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  45.  35
    A network of paths toward innovation.Jeremy A. Draghi & Joshua B. Plotkin - 2012 - Bioessays 34 (6):518-520.
  46.  41
    A Rational Analysis of Rule‐Based Concept Learning.Noah D. Goodman, Joshua B. Tenenbaum, Jacob Feldman & Thomas L. Griffiths - 2008 - Cognitive Science 32 (1):108-154.
    This article proposes a new model of human concept learning that provides a rational analysis of learning feature‐based concepts. This model is built upon Bayesian inference for a grammatically structured hypothesis space—a concept language of logical rules. This article compares the model predictions to human generalization judgments in several well‐known category learning experiments, and finds good agreement for both average and individual participant generalizations. This article further investigates judgments for a broad set of 7‐feature concepts—a more natural setting in several (...)
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  47.  16
    Drift as a Driver of Language Change: An Artificial Language Experiment.Rafael Ventura, Joshua B. Plotkin & Gareth Roberts - 2022 - Cognitive Science 46 (9):e13197.
    Over half a century ago, George Zipf observed that more frequent words tend to be older. Corpus studies since then have confirmed this pattern, with more frequent words being replaced and regularized less often than less frequent words. Two main hypotheses have been proposed to explain this: that frequent words change less because selection against innovation is stronger at higher frequencies, or that they change less because stochastic drift is stronger at lower frequencies. Here, we report the first experimental test (...)
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  48.  32
    Bayesian collective learning emerges from heuristic social learning.P. M. Krafft, Erez Shmueli, Thomas L. Griffiths, Joshua B. Tenenbaum & Alex “Sandy” Pentland - 2021 - Cognition 212 (C):104469.
  49.  35
    9. How recursive is language? A Bayesian exploration.Amy Perfors, Joshua B. Tenenbaum, Edward Gibson & Terry Regier - 2010 - In Harry van der Hulst (ed.), Recursion and Human Language. De Gruyter Mouton. pp. 159-176.
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  50.  49
    A probabilistic model of theory formation.Charles Kemp, Joshua B. Tenenbaum, Sourabh Niyogi & Thomas L. Griffiths - 2010 - Cognition 114 (2):165-196.
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