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  1. Précis ofBeyond modularity: A developmental perspective on cognitive science.Annette Karmiloff-Smith -1994 -Behavioral and Brain Sciences 17 (4):693-707.
    Beyond modularityattempts a synthesis of Fodor's anticonstructivist nativism and Piaget's antinativist constructivism. Contra Fodor, I argue that: (1) the study of cognitive development is essential to cognitive science, (2) the module/central processing dichotomy is too rigid, and (3) the mind does not begin with prespecified modules; rather, development involves a gradual process of “modularization.” Contra Piaget, I argue that: (1) development rarely involves stagelike domain-general change and (2) domainspecific predispositions give development a small but significant kickstart by focusing the infant's (...) attention on proprietary inputs. Development does not stop at efficient learning. A fundamental aspect of human development (“representational redescription”) is the hypothesized process by which information that isina cognitive system becomes progressively explicit knowledgetothat system. Development thus involves two complementary processes of progressive modularization and progressive “explicitation.” Empirical findings on the child as linguist, physicist, mathematician, psychologist, and notator are discussed in support of the theoretical framework. Each chapter concentrates first on the initial state of the infant mind/brain and on subsequent domain-specific learning in infancy and early childhood. It then goes on to explore data on older children's problem solving and theory building, with particular focus on evolving cognitive flexibility. Emphasis is placed throughout on the status of representations underlying different capacities and on the multiple levels at which knowledge is stored and accessible. Finally, consideration is given to the need for more formal developmental models, and a comparison is made between representational redescription and connectionist simulations of development. In conclusion, I consider what is special about human cognition by speculating on the status of representations underlying the structure of behavior in other species. (shrink)
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  • Varieties of numerical abilities.Stanislas Dehaene -1992 -Cognition 44 (1-2):1-42.
  • The construction of large number representations in adults.Elizabeth Spelke &Hilary Barth -2003 -Cognition 86 (3):201-221.
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  • From overt behavior to hypothetical behavior to memory: Inference in the wrong direction.Howard Rachlin -1994 -Behavioral and Brain Sciences 17 (1):147-148.
  • Species and individual differences in communication based on private states.David Lubinski &Travis Thompson -1993 -Behavioral and Brain Sciences 16 (4):627-642.
    The way people come to report private stimulation (e.g., feeling states) arising within their own bodies is not well understood. Although the Darwinian assumption of biological continuity has been the basis of extensive animal modeling for many human biological and behavioral phenomena, few have attempted to model human communication based on private stimulation. This target article discusses such an animal model using concepts and methods derived from the study of discriminative stimulus effects of drugs and recent research on interanimal communication. (...) We discuss how humans acquire the capacity to identify and report private stimulation and we analyze intra- and interspecies differences in neurochemical mechanisms for transducing interoceptive stimuli, enzymatic and other metabolic factors, learning ability, and discrimination learning histories and their relation to psychiatric and developmental disabilities. (shrink)
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  • Language and number: a bilingual training study.Elizabeth S. Spelke -2001 -Cognition 78 (1):45-88.
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  • Précis of the number sense.Stanislas Dehaene -2001 -Mind and Language 16 (1):16–36.
    ‘Number sense’ is a short‐hand for our ability to quickly understand, approximate, and manipulate numerical quantities. My hypothesis is that number sense rests on cerebral circuits that have evolved specifically for the purpose of representing basic arithmetic knowledge. Four lines of evidence suggesting that number sense constitutes a domain‐specific, biologically‐determined ability are reviewed: the presence of evolutionary precursors of arithmetic in animals; the early emergence of arithmetic competence in infants independently of other abilities, including language; the existence of a homology (...) between the animal, infant, and human adult abilities for number processing; and the existence of a dedicated cerebral substrate. In adults of all cultures, lesions to the inferior parietal region can specifically impair number sense while leaving the knowledge of other cognitive domains intact. Furthermore, this region is demonstrably activated during number processing. I postulate that higher–level cultural devel‐opments in arithmetic emerge through the establishment of linkages between this core analogical representation and other verbal and visual representations of number notations. The neural and cognitive organization of those representations can explain why some mathematical concepts are intuitive, while others are so difficult to grasp. Thus, the ultimate foundations of mathematics rests on core representations that have been internalized in our brains through evolution. (shrink)
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  • Psychological foundations of number: numerical competence in human infants.Karen Wynn -1998 -Trends in Cognitive Sciences 2 (8):296-303.
  • Countable entities: Developmental changes.Elizabeth F. Shipley &Barbara Shepperson -1990 -Cognition 34 (2):109-136.
  • The role of convention in the communication of private events.Chris Moore -1993 -Behavioral and Brain Sciences 16 (4):656-657.
  • Spontaneous number discrimination of multi-format auditory stimuli in cotton-top tamarins.Marc D. Hauser,Stanislas Dehaene,Ghislaine Dehaene-Lambertz &Andrea L. Patalano -2002 -Cognition 86 (2):B23-B32.
  • Numbers and Arithmetic: Neither Hardwired Nor Out There.Rafael Núñez -2009 -Biological Theory 4 (1):68-83.
    What is the nature of number systems and arithmetic that we use in science for quantification, analysis, and modeling? I argue that number concepts and arithmetic are neither hardwired in the brain, nor do they exist out there in the universe. Innate subitizing and early cognitive preconditions for number— which we share with many other species—cannot provide the foundations for the precision, richness, and range of number concepts and simple arithmetic, let alone that of more complex mathematical concepts. Numbers and (...) arithmetic, and mathematics in general, have unique features—precision, objectivity, rigor, generalizability, stability, symbolizability, and applicability to the real world—that must be accounted for. They are sophisticated concepts that developed culturally only in recent human history. I suggest that numbers and arithmetic are realized through precise combinations of non-mathematical everyday cognitive mechanisms that make human imagination and abstraction possible. One such mechanism, conceptual metaphor, is a neurally instantiated inference-preserving cross-domain mapping that allows the conceptualization of abstract entities in terms of grounded bodily experience. I analyze how the inferential organization of the properties and “laws” of arithmetic emerge metaphorically from everyday meaningful actions. Numbers and arithmetic are thus—outside of natural selection—the product of the biologically constrained interaction of individuals with the appropriate cultural and historical phenotypic variation supported by language, writing systems, and education. (shrink)
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  • Animal concepts: Content and discontent.Nick Chater &Cecilia Heyes -1994 -Mind and Language 9 (3):209-246.
  • Arthropod Intelligence? The Case for Portia.Fiona R. Cross,Georgina E. Carvell,Robert R. Jackson &Randolph C. Grace -2020 -Frontiers in Psychology 11:568049.
    Macphail’s “null hypothesis,” that there are no differences in intelligence, qualitative, or quantitative, between non-human vertebrates has been controversial. This controversy can be useful if it encourages interest in acquiring a detailed understanding of how non-human animals express flexible problem-solving capacity (“intelligence”), but limiting the discussion to vertebrates is too arbitrary. As an example, we focus here on Portia, a spider with an especially intricate predatory strategy and a preference for other spiders as prey. We review research on pre-planned detours, (...) expectancy violation, and a capacity to solve confinement problems where, in each of these three contexts, there is experimental evidence of innate cognitive capacities and reliance on internal representation. These cognitive capacities are related to, but not identical to, intelligence. When discussing intelligence, as when discussing cognition, it is more useful to envisage a continuum instead of something that is simply present or not; in other words, a continuum pertaining to flexible problem-solving capacity for “intelligence” and a continuum pertaining to reliance on internal representation for “cognition.” When envisaging a continuum pertaining to intelligence, Daniel Dennett’s notion of four Creatures (Darwinian, Skinnerian, Popperian, and Gregorian) is of interest, with the distinction between Skinnerian and Popperian Creatures being especially relevant when considering Portia. When we consider these distinctions, a case can be made for Portia being a Popperian Creature. Like Skinnerian Creatures, Popperian Creatures express flexible problem solving capacity, but the manner in which this capacity is expressed by Popperian Creatures is more distinctively cognitive. (shrink)
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  • Number versus continuous quantity in numerosity judgments by fish.Christian Agrillo,Laura Piffer &Angelo Bisazza -2011 -Cognition 119 (2):281-287.
    In quantity discrimination tasks, adults, infants and animals have been sometimes observed to process number only after all continuous variables, such as area or density, have been controlled for. This has been taken as evidence that processing number may be more cognitively demanding than processing continuous variables. We tested this hypothesis by training mosquitofish to discriminate two items from three in three different conditions. In one condition, continuous variables were controlled while numerical information was available; in another, the number was (...) kept constant and information relating to continuous variables was available; in the third condition, stimuli differed for both number and continuous quantities. Fish learned to discriminate more quickly when both number and continuous information were available compared to when they could use continuous information only or number only; there was no difference in the learning rate between the two latter conditions. Our results do not support the hypothesis that processing numbers imposes a higher cognitive load than processing continuous variables. Rather, they suggest that availability of multiple information sources may facilitate discrimination learning. (shrink)
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  • Re-establishing the distinction between numerosity, numerousness, and number in numerical cognition.César Frederico Dos Santos -2022 -Philosophical Psychology 35 (8):1152-1180.
    In 1939, the influential psychophysicist S. S. Stevens proposed definitional distinctions between the terms ‘number,’ ‘numerosity,’ and ‘numerousness.’ Although the definitions he proposed were adopted by syeveral psychophysicists and experimental psychologists in the 1940s and 1950s, they were almost forgotten in the subsequent decades, making room for what has been described as a “terminological chaos” in the field of numerical cognition. In this paper, I review Stevens’s distinctions to help bring order to this alleged chaos and to shed light on (...) two closely related questions: whether it is adequate to speak of a number sense and how philosophers can make sense of the claim by cognitive scientists that numbers are perceptual entities. Moreover, I offer further support to Stevens’s distinction between numerosity and numerousness by showing that they are relational properties that emerge through different relationships between agents and their environments. The final conclusion is that, by adopting Stevens’s distinctions, numbers do not need to be seen as perceptual entities, since the so-called number sense is better described as a sense of numerousness. (shrink)
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  • Sexual selection and sex differences in mathematical abilities.David C. Geary -1996 -Behavioral and Brain Sciences 19 (2):229-247.
    The principles of sexual selection were used as an organizing framework for interpreting cross-national patterns of sex differences in mathematical abilities. Cross-national studies suggest that there are no sex differences in biologically primary mathematical abilities, that is, for those mathematical abilities that are found in all cultures as well as in nonhuman primates, and show moderate heritability estimates. Sex differences in several biologically secondary mathematical domains (i.e., those that emerge primarily in school) are found throughout the industrialized world. In particular, (...) males consistently outperform females in the solving of mathematical word problems and geometry. Sexual selection and any associated proximate mechanisms (e.g., sex hormones) influence these sex differences in mathematical performance indirectly. First, sexual selection resulted in greater elaboration in males than in females of the neurocognitive systems that support navigation in three-dimensional space. Knowledge implicit in these systems reflects an understanding of basic Euclidean geometry, and may thus be one source of the male advantage in geometry. Males also use more readily than females these spatial systems in problem-solving situations, which provides them with an advantage in solving word problems and geometry. In addition, sex differences in social styles and interests, which also appear to be related in part to sexual selection, result in sex differences in engagement iii mathematics-related activities, thus further increasing the male advantage in certain mathematical domains. A model that integrates these biological influences with sociocultural influences on the sex differences in mathematical performance is presented in this article. (shrink)
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  • Representation of the cardinality principle: early conception of error in a counterfactual test.Norman H. Freeman,Cristina Antonucci &Charlie Lewis -2000 -Cognition 74 (1):71-89.
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  • Searching for the Critical p of Macphail’s Null Hypothesis: The Contribution of Numerical Abilities of Fish.Maria Elena Miletto Petrazzini,Alessandra Pecunioso,Marco Dadda &Christian Agrillo -2020 -Frontiers in Psychology 11.
  • Towards a Darwinian approach to mathematics.Helen De Cruz -2006 -Foundations of Science 11 (1):157-196.
    In the past decades, recent paradigm shifts in ethology, psychology, and the social sciences have given rise to various new disciplines like cognitive ethology and evolutionary psychology. These disciplines use concepts and theories of evolutionary biology to understand and explain the design, function and origin of the brain. I shall argue that there are several good reasons why this approach could also apply to human mathematical abilities. I will review evidence from various disciplines (cognitive ethology, cognitive psychology, cognitive archaeology and (...) neuropsychology) that suggests that the human capacity for mathematics is a category-specific domain of knowledge, hard-wired in the brain, which can be explained as the result of natural selection. (shrink)
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  • Beyond modularity: Neural evidence for constructivist principles in development.Steven R. Quartz &Terrence J. Sejnowski -1994 -Behavioral and Brain Sciences 17 (4):725-726.
  • Representation: Ontogenesis and phylogenesis.Merlin Donald -1994 -Behavioral and Brain Sciences 17 (4):714-715.
  • Representational redescription, memory, and connectionism.P. J. Hampson -1994 -Behavioral and Brain Sciences 17 (4):721-721.
  • Innate and Cultural Spatial Time: A Developmental Perspective.Barbara Magnani &Alessandro Musetti -2017 -Frontiers in Human Neuroscience 11.
    We reviewed literature to understand when a spatial map for time is available in the brain. We carefully defined the concepts of metrical map of time and of conceptual representation of time as the mental time line (MTL) in order to formulate our position. It is that both metrical map and conceptual representation of time are spatial in nature. The former should be innate, related to motor/implicit timing, it should represent all magnitudes with an analogic and bi-dimensional structure. The latter (...) MTL should be learned, available at about 8–10 years-old and related to cognitive/explicit time. It should have uni-dimensional, linear and directional structure (left-to-right in Western culture). We bear the centrality of the development of number cognition, of time semantic concepts and of reading/writing habits for the development of ordinality and linearity of the MTL. (shrink)
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  • The perception of quantity ain't number: Missing the primacy of symbolic reference.Rafael E. Núñez,Francesco D'Errico,Russell D. Gray &Andrea Bender -2021 -Behavioral and Brain Sciences 44.
    Clarke and Beck's defense of the theoretical construct “approximate number system” is flawed in serious ways – from biological misconceptions to mathematical naïveté. The authors misunderstand behavioral/psychological technical concepts, such as numerosity and quantical cognition, which they disdain as “exotic.” Additionally, their characterization of rational numbers is blind to the essential role of symbolic reference in the emergence of number.
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  • Perceived numerosity as a function of array number, speed of array development, and density of array items.Walter H. Hollingsworth,J. Paul Simmons,Tammy R. Coates &Henry A. Cross -1991 -Bulletin of the Psychonomic Society 29 (5):448-450.
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  • Is there an implicit level of representation?Annie Vinter &Pierre Perruchet -1994 -Behavioral and Brain Sciences 17 (4):730-731.
  • Mathematical principles of reinforcement.Peter R. Killeen -1994 -Behavioral and Brain Sciences 17 (1):105-135.
    Effective conditioning requires a correlation between the experimenter's definition of a response and an organism's, but an animal's perception of its behavior differs from ours. These experiments explore various definitions of the response, using the slopes of learning curves to infer which comes closest to the organism's definition. The resulting exponentially weighted moving average provides a model of memory that is used to ground a quantitative theory of reinforcement. The theory assumes that: incentives excite behavior and focus the excitement on (...) responses that are contemporaneous in memory. The correlation between the organism's memory and the behavior measured by the experimenter is given by coupling coefficients, which are derived for various schedules of reinforcement. The coupling coefficients for simple schedules may be concatenated to predict the effects of complex schedules. The coefficients are inserted into a generic model of arousal and temporal constraint to predict response rates under any scheduling arrangement. The theory posits a response-indexed decay of memory, not a time-indexed one. It requires that incentives displace memory for the responses that occur before them, and may truncate the representation of the response that brings them about. As a contiguity-weighted correlation model, it bridges opposing views of the reinforcement process. By placing the short-term memory of behavior in so central a role, it provides a behavioral account of a key cognitive process. (shrink)
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  • Animal Cognition, Species Invariantism, and Mathematical Realism.Helen De Cruz -2019 - In Andrew Aberdein & Matthew Inglis,Advances in Experimental Philosophy of Logic and Mathematics. London: Bloomsbury Academic. pp. 39-61.
    What can we infer from numerical cognition about mathematical realism? In this paper, I will consider one aspect of numerical cognition that has received little attention in the literature: the remarkable similarities of numerical cognitive capacities across many animal species. This Invariantism in Numerical Cognition (INC) indicates that mathematics and morality are disanalogous in an important respect: proto-moral beliefs differ substantially between animal species, whereas proto-mathematical beliefs (at least in the animals studied) seem to show more similarities. This makes moral (...) beliefs more susceptible to a contingency challenge from evolution compared to mathematical beliefs, and indicates that mathematical beliefs might be less vulnerable to evolutionary debunking arguments. I will then examine to what extent INC can be used to flesh out a positive case for mathematical realism. Finally, I will review two forms of mathematical realism that are promising in the light of the evolutionary evidence about numerical cognition, ante rem structuralism and Millean empiricism. (shrink)
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  • Is mathematical competence innate?Robert Schwartz -1995 -Philosophy of Science 62 (2):227-40.
    Despite a vast philosophical literature on the epistemology of mathematics and much speculation about how, in principle, knowledge of this domain is possible, little attention has been paid to the psychological findings and theories concerning the acquisition, comprehension and use of mathematical knowledge. This contrasts sharply with recent philosophical work on language where comparable issues and problems arise. One topic that is the center of debate in the study of mathematical cognition is the question of innateness. This paper critically examines (...) the controversy. (shrink)
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  • Towards a Darwinian Approach to Mathematics.Helen Cruz -2006 -Foundations of Science 11 (1):157-196.
    In the past decades, recent paradigm shifts in ethology, psychology, and the social sciences have given rise to various new disciplines like cognitive ethology and evolutionary psychology. These disciplines use concepts and theories of evolutionary biology to understand and explain the design, function and origin of the brain. I shall argue that there are several good reasons why this approach could also apply to human mathematical abilities. I will review evidence from various disciplines (cognitive ethology, cognitive psychology, cognitive archaeology and (...) neuropsychology) that suggests that the human capacity for mathematics is a category-specific domain of knowledge, hard-wired in the brain, which can be explained as the result of natural selection. (shrink)
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  • The real problem with constructivism.Paul Bloom &Karen Wynn -1994 -Behavioral and Brain Sciences 17 (4):707-708.
  • The response problem.Robert C. Bolles -1994 -Behavioral and Brain Sciences 17 (1):135-136.
  • Animal-centered models of reinforcement.William Timberlake -1994 -Behavioral and Brain Sciences 17 (1):153-154.
  • The contribution of fish studies to the “number sense” debate.Christian Agrillo &Angelo Bisazza -2017 -Behavioral and Brain Sciences 40.
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  • Perhaps Sisyphus is the relevant model for animal-language researchers.Donald M. Baer -1993 -Behavioral and Brain Sciences 16 (4):642-643.
  • The status of private events in behavior analysis.William M. Baum -1993 -Behavioral and Brain Sciences 16 (4):644-644.
  • A Fodorian guide to Switzerland: Jung and Piaget combined?Péter Bodor &Csaba Pléh -1994 -Behavioral and Brain Sciences 17 (4):709-710.
  • Communication and internal states: What is their relationship?Michael Bamberg -1993 -Behavioral and Brain Sciences 16 (4):643-644.
    Common folks “have” emotions and talk to others; and sometimes they make “their” emotions the topic of such talk. The emotions seem to be “theirs,” since they can be conceived of as private states (or events); and they can be topicalized, because we seem to be able to attribute or lend a conventionalized public form (such as a linguistic label or name) to some inner (and therefore nonpublic) state or event. This is the way much of our folk-talk and folk-thinking (...) about emotions, the expression thereof, the role of language in these expressions, and communication in general are organized. However, as we have shown (Bamberg & Lindenberger 1984), such talk serves the purpose of communicating effectively and reaching mutual understanding. (shrink)
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  • Representational redescription: A question of sequence.Margaret A. Boden -1994 -Behavioral and Brain Sciences 17 (4):708-708.
  • The outside route to the inside story.Marc N. Branch -1993 -Behavioral and Brain Sciences 16 (4):644-645.
  • Validation of behavioural equations: Can neurobiology help?C. M. Bradshaw -1994 -Behavioral and Brain Sciences 17 (1):136-137.
  • Animal communication of private states does not illuminate the human case.Selmer Bringsjord &Elizabeth Bringsjord -1993 -Behavioral and Brain Sciences 16 (4):645-646.
  • A test for S-S associations in a conditional counting task.Richard A. Burns &Frances A. Nesbitt -1990 -Bulletin of the Psychonomic Society 28 (5):441-444.
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  • What's getting redescribed?Robert L. Campbell -1994 -Behavioral and Brain Sciences 17 (4):710-711.
  • Plausible reconstruction? No!E. J. Capaldi &Robert W. Proctor -1993 -Behavioral and Brain Sciences 16 (4):646-647.
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  • (1 other version)Representational redescription and cognitive architectures.Antonella Carassa &Maurizio Tirassa -1994 -Behavioral and Brain Sciences 17 (4):711-712.
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  • Do gender differences in spatial skills mediate gender differences in mathematics among high-ability students?M. Beth Casey -1996 -Behavioral and Brain Sciences 19 (2):247-248.
    Based on Geary's theory, intelligence may determine which males utilize innate spatial knowledge to inform their mathematical solutions. This may explain why math gender differences occur mainly with higher abilities. In support, we found that mental rotation ability served as a mediator of gender differences on the math Scholastic Assessment Test for two high-ability samples. Our research suggests, however, that environment and biology interact to influence mental rotation abilities.
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  • Still far too sexy a topic.Susan F. Chipman -1996 -Behavioral and Brain Sciences 19 (2):248-249.
    Geary is highly selective in his use of the literature on gender differences. His assumption of consistent female inferiority in mathematics is not necessarily supported by the facts.
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  • All sex differences in cognitive ability may be explained by an X-Y homologous gene determining degrees of cerebral asymmetry.T. J. Crow -1996 -Behavioral and Brain Sciences 19 (2):249-250.
    Male superiority in mathematical ability (along with female superiority in verbal fluency) may reflect the operation of an X-Y homologous gene (the right-shift-factor) influencing the relative rates of development of the cerebral hemispheres. Alleles at the locus on the Y chromosome will be selected at a later mean age than alleles on the X, and only by females.
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