Search results for 'word' (try it on Scholar)

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Bibliography: Words in Philosophy of Language
  1.  28
    Kenny Smith, Andrew D. M. Smith & Richard A. Blythe (2011). Cross-Situational Learning: An Experimental Study of Word-Learning Mechanisms. Cognitive Science 35 (3):480-498.
    Cross-situational learning is a mechanism for learning the meaning of words across multiple exposures, despite exposure-by-exposure uncertainty as to the word's true meaning. We present experimental evidence showing that humans learn words effectively using cross-situational learning, even at high levels of referential uncertainty. Both overall success rates and the time taken to learn words are affected by the degree of referential uncertainty, with greater referential uncertainty leading to less reliable, slower learning. Words are also learned less successfully and more (...)
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  2.  13
    Daniel Yurovsky, Chen Yu & Linda B. Smith (2013). Competitive Processes in Cross‐Situational Word Learning. Cognitive Science 37 (5):891-921.
    Cross-situational word learning, like any statistical learning problem, involves tracking the regularities in the environment. However, the information that learners pick up from these regularities is dependent on their learning mechanism. This article investigates the role of one type of mechanism in statistical word learning: competition. Competitive mechanisms would allow learners to find the signal in noisy input and would help to explain the speed with which learners succeed in statistical learning tasks. Because cross-situational word learning provides (...)
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  3.  27
    Afsaneh Fazly, Afra Alishahi & Suzanne Stevenson (2010). A Probabilistic Computational Model of Cross-Situational Word Learning. Cognitive Science 34 (6):1017-1063.
    Words are the essence of communication: They are the building blocks of any language. Learning the meaning of words is thus one of the most important aspects of language acquisition: Children must first learn words before they can combine them into complex utterances. Many theories have been developed to explain the impressive efficiency of young children in acquiring the vocabulary of their language, as well as the developmental patterns observed in the course of lexical acquisition. A major source of disagreement (...)
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  4.  14
    Haley A. Vlach & Catherine M. Sandhofer (2014). Retrieval Dynamics and Retention in Cross‐Situational Statistical Word Learning. Cognitive Science 38 (4):757-774.
    Previous research on cross-situational word learning has demonstrated that learners are able to reduce ambiguity in mapping words to referents by tracking co-occurrence probabilities across learning events. In the current experiments, we examined whether learners are able to retain mappings over time. The results revealed that learners are able to retain mappings for up to 1 week later. However, there were interactions between the amount of retention and the different learning conditions. Interestingly, the strongest retention was associated with a (...)
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  5.  30
    Stanka A. Fitneva & Morten H. Christiansen (2011). Looking in the Wrong Direction Correlates With More Accurate Word Learning. Cognitive Science 35 (2):367-380.
    Previous research on lexical development has aimed to identify the factors that enable accurate initial word-referent mappings based on the assumption that the accuracy of initial word-referent associations is critical for word learning. The present study challenges this assumption. Adult English speakers learned an artificial language within a cross-situational learning paradigm. Visual fixation data were used to assess the direction of visual attention. Participants whose longest fixations in the initial trials fell more often on distracter images performed (...)
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  6.  8
    Jonathan F. Kominsky & Frank C. Keil (2014). Overestimation of Knowledge About Word Meanings: The “Misplaced Meaning” Effect. Cognitive Science 38 (8):1604-1633.
    Children and adults may not realize how much they depend on external sources in understanding word meanings. Four experiments investigated the existence and developmental course of a “Misplaced Meaning” effect, wherein children and adults overestimate their knowledge about the meanings of various words by underestimating how much they rely on outside sources to determine precise reference. Studies 1 and 2 demonstrate that children and adults show a highly consistent MM effect, and that it is stronger in young children. Study (...)
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  7.  9
    Catriona Silvey, Simon Kirby & Kenny Smith (2015). Word Meanings Evolve to Selectively Preserve Distinctions on Salient Dimensions. Cognitive Science 39 (1):212-226.
    Words refer to objects in the world, but this correspondence is not one-to-one: Each word has a range of referents that share features on some dimensions but differ on others. This property of language is called underspecification. Parts of the lexicon have characteristic patterns of underspecification; for example, artifact nouns tend to specify shape, but not color, whereas substance nouns specify material but not shape. These regularities in the lexicon enable learners to generalize new words appropriately. How does the (...)
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  8.  5
    Ołena Łucyszyna (2016). Classical Sāṁkhya on the Relationship Between a Word and Its Meaning. Journal of Indian Philosophy 44 (2):303-323.
    The aim of this article is to reconstruct the classical Sāṁkhya view on the relationship between a word and its meaning. The study embraces all the extant texts of classical Sāṁkhya, but it is based mainly on the Yuktidīpikā, since this commentary contains most of the fragments which are directly related to the topic of our research. The textual analysis has led me to the following conclusion. It is possible to reconstruct two different and conflicting views on the relationship (...)
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  9.  1
    Judith Koehne & Matthew W. Crocker (2015). The Interplay of Cross‐Situational Word Learning and Sentence‐Level Constraints. Cognitive Science 39 (5):849-889.
    A variety of mechanisms contribute to word learning. Learners can track co-occurring words and referents across situations in a bottom-up manner. Equally, they can exploit sentential contexts, relying on top–down information such as verb–argument relations and world knowledge, offering immediate constraints on meaning. When combined, CSWL and SLCL potentially modulate each other's influence, revealing how word learners deal with multiple mechanisms simultaneously: Do they use all mechanisms? Prefer one? Is their strategy context dependent? Three experiments conducted with adult (...)
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  10.  26
    Janet H. Hsiao & Sze Man Lam (2013). The Modulation of Visual and Task Characteristics of a Writing System on Hemispheric Lateralization in Visual Word Recognition—A Computational Exploration. Cognitive Science 37 (5):861-890.
    Through computational modeling, here we examine whether visual and task characteristics of writing systems alone can account for lateralization differences in visual word recognition between different languages without assuming influence from left hemisphere (LH) lateralized language processes. We apply a hemispheric processing model of face recognition to visual word recognition; the model implements a theory of hemispheric asymmetry in perception that posits low spatial frequency biases in the right hemisphere and high spatial frequency (HSF) biases in the LH. (...)
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  11.  30
    Katerina Kantartzis, Mutsumi Imai & Sotaro Kita (2011). Japanese Sound-Symbolism Facilitates Word Learning in English-Speaking Children. Cognitive Science 35 (3):575-586.
    Sound-symbolism is the nonarbitrary link between the sound and meaning of a word. Japanese-speaking children performed better in a verb generalization task when they were taught novel sound-symbolic verbs, created based on existing Japanese sound-symbolic words, than novel nonsound-symbolic verbs (Imai, Kita, Nagumo, & Okada, 2008). A question remained as to whether the Japanese children had picked up regularities in the Japanese sound-symbolic lexicon or were sensitive to universal sound-symbolism. The present study aimed to provide support for the latter. (...)
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  12.  2
    Kevin J. Riggs, Emily Mather, Grace Hyde & Andrew Simpson (2016). Parallels Between Action‐Object Mapping and Word‐Object Mapping in Young Children. Cognitive Science 40 (4):992-1006.
    Across a series of four experiments with 3- to 4-year-olds we demonstrate how cognitive mechanisms supporting noun learning extend to the mapping of actions to objects. In Experiment 1 the demonstration of a novel action led children to select a novel, rather than a familiar object. In Experiment 2 children exhibited long-term retention of novel action-object mappings and extended these actions to other category members. In Experiment 3 we showed that children formed an accurate sensorimotor record of the novel action. (...)
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  13.  21
    Sumarga H. Suanda & Laura L. Namy (2012). Detailed Behavioral Analysis as a Window Into Cross-Situational Word Learning. Cognitive Science 36 (3):545-559.
    Recent research has demonstrated that word learners can determine word-referent mappings by tracking co-occurrences across multiple ambiguous naming events. The current study addresses the mechanisms underlying this capacity to learn words cross-situationally. This replication and extension of Yu and Smith (2007) investigates the factors influencing both successful cross-situational word learning and mis-mappings. Item analysis and error patterns revealed that the co-occurrence structure of the learning environment as well as the context of the testing environment jointly affected learning (...)
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  14.  18
    Sergio Román & Pedro J. Cuestas (2008). The Perceptions of Consumers Regarding Online Retailers' Ethics and Their Relationship with Consumers' General Internet Expertise and Word of Mouth: A Preliminary Analysis. [REVIEW] Journal of Business Ethics 83 (4):641 - 656.
    Ethical concerns of Internet users continue to rise. Accordingly, several scholars have called for systematic empirical research to address these issues. This study examines the conceptualization and measurement of consumers' perceptions regarding the ethics of online retailers (CPEOR). Also, this research represents a first step into the analysis of the relationship between CPEOR, consumers' general Internet expertise and reported positive word of mouth (WOM). Results, from a convenience sample of 357 online shoppers, suggest that CPEOR can be operationalized as (...)
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  15.  3
    George Kachergis, Chen Yu & Richard M. Shiffrin (2016). A Bootstrapping Model of Frequency and Context Effects in Word Learning. Cognitive Science 40 (4).
    Prior research has shown that people can learn many nouns from a short series of ambiguous situations containing multiple words and objects. For successful cross-situational learning, people must approximately track which words and referents co-occur most frequently. This study investigates the effects of allowing some word-referent pairs to appear more frequently than others, as is true in real-world learning environments. Surprisingly, high-frequency pairs are not always learned better, but can also boost learning of other pairs. Using a recent associative (...)
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  16.  23
    Keith S. Apfelbaum & Bob McMurray (2011). Using Variability to Guide Dimensional Weighting: Associative Mechanisms in Early Word Learning. Cognitive Science 35 (6):1105-1138.
    At 14 months, children appear to struggle to apply their fairly well-developed speech perception abilities to learning similar sounding words (e.g., bih/dih; Stager & Werker, 1997). However, variability in nonphonetic aspects of the training stimuli seems to aid word learning at this age. Extant theories of early word learning cannot account for this benefit of variability. We offer a simple explanation for this range of effects based on associative learning. Simulations suggest that if infants encode both noncontrastive information (...)
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  17.  3
    Tomas Engelthaler & Thomas T. Hills (2016). Feature Biases in Early Word Learning: Network Distinctiveness Predicts Age of Acquisition. Cognitive Science 40 (4).
    Do properties of a word's features influence the order of its acquisition in early word learning? Combining the principles of mutual exclusivity and shape bias, the present work takes a network analysis approach to understanding how feature distinctiveness predicts the order of early word learning. Distance networks were built from nouns with edge lengths computed using various distance measures. Feature distinctiveness was computed as a distance measure, showing how far an object in a network is from other (...)
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  18.  4
    Frédéric Vallée-Tourangeau & Miles Wrightman (2010). Interactive Skills and Individual Differences in a Word Production Task. AI and Society 25 (4):433-439.
    In attempting to solve a wide variety of tasks, people naturally seek to modify their external environment such that the physical space in which they work is more amenable or ‘congenial’ to achieving a desired outcome. Attempts to determine the effectiveness of certain artifacts or spatial reorganizations in aiding reasoners solve problems must be relativised to the difficulty of the task and the cognitive abilities of the reasoners. These factors were examined using a simple word production task with letter (...)
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  19.  22
    Timothy Pritchard (2013). Locke and the Primary Signification of Words: An Approach to Word Meaning. British Journal for the History of Philosophy 21 (3):486-506.
    Locke’s claim that the primary signification of (most) words is an idea, or complex of ideas, has received different interpretations. I support the majority view that Locke’s notion of primary signification can be construed in terms of linguistic meaning. But this reading has been seen as making Locke’s account vulnerable to various criticisms, of which I consider two. First, it appears to make the account vulnerable to the charge that an idea cannot play the role that a word meaning (...)
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  20.  28
    Dawn M. McBride & B. Dosher (2002). A Comparison of Conscious and Automatic Memory Processes for Picture and Word Stimuli: A Process Dissocation Analysis. Consciousness and Cognition 11 (3):423-460.
    Four experiments were conducted to evaluate explanations of picture superiority effects previously found for several tasks. In a process dissociation procedure with word stem completion, picture fragment completion, and category production tasks, conscious and automatic memory processes were compared for studied pictures and words with an independent retrieval model and a generate-source model. The predictions of a transfer appropriate processing account of picture superiority were tested and validated in “process pure” latent measures of conscious and unconscious, or automatic and (...)
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  21.  24
    Matthew Brown & Derek Besner (2002). Semantic Priming: On the Role of Awareness in Visual Word Recognition in the Absence of an Expectancy. Consciousness and Cognition 11 (3):402-422.
    By hypothesis, awareness is involved in the modulation of feedback from semantics to the lexical level in the visual word recognition system. When subjects are aware of the fact that there are many related prime–target pairs in a semantic priming experiment, this knowledge is used to configure the system to feed activation back from semantics to the lexical level so as to facilitate processing. When subjects are unaware of this fact, the default set is maintained in which activation is (...)
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  22.  35
    Thomas Hannagan & Jonathan Grainger (2012). Protein Analysis Meets Visual Word Recognition: A Case for String Kernels in the Brain. Cognitive Science 36 (4):575-606.
    It has been recently argued that some machine learning techniques known as Kernel methods could be relevant for capturing cognitive and neural mechanisms (Jäkel, Schölkopf, & Wichmann, 2009). We point out that ‘‘String kernels,’’ initially designed for protein function prediction and spam detection, are virtually identical to one contending proposal for how the brain encodes orthographic information during reading. We suggest some reasons for this connection and we derive new ideas for visual word recognition that are successfully put to (...)
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  23.  6
    Paola Escudero, Karen E. Mulak & Haley A. Vlach (2016). Cross‐Situational Learning of Minimal Word Pairs. Cognitive Science 40 (2):455-465.
    Cross-situational statistical learning of words involves tracking co-occurrences of auditory words and objects across time to infer word-referent mappings. Previous research has demonstrated that learners can infer referents across sets of very phonologically distinct words, but it remains unknown whether learners can encode fine phonological differences during cross-situational statistical learning. This study examined learners’ cross-situational statistical learning of minimal pairs that differed on one consonant segment, minimal pairs that differed on one vowel segment, and non-minimal pairs that differed on (...)
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  24.  3
    Thomas M. Gruenenfelder, Gabriel Recchia, Tim Rubin & Michael N. Jones (2015). Graph‐Theoretic Properties of Networks Based on Word Association Norms: Implications for Models of Lexical Semantic Memory. Cognitive Science 40 (1):n/a-n/a.
    We compared the ability of three different contextual models of lexical semantic memory and of a simple associative model to predict the properties of semantic networks derived from word association norms. None of the semantic models were able to accurately predict all of the network properties. All three contextual models over-predicted clustering in the norms, whereas the associative model under-predicted clustering. Only a hybrid model that assumed that some of the responses were based on a contextual model and others (...)
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  25.  26
    Katherine Yoshida, Mijke Rhemtulla & Athena Vouloumanos (2012). Exclusion Constraints Facilitate Statistical Word Learning. Cognitive Science 36 (5):933-947.
    The roles of linguistic, cognitive, and social-pragmatic processes in word learning are well established. If statistical mechanisms also contribute to word learning, they must interact with these processes; however, there exists little evidence for such mechanistic synergy. Adults use co-occurrence statistics to encode speech–object pairings with detailed sensitivity in stochastic learning environments (Vouloumanos, 2008). Here, we replicate this statistical work with nonspeech sounds and compare the results with the previous speech studies to examine whether exclusion constraints contribute equally (...)
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  26.  4
    Kevin J. Riggs, Emily Mather, Grace Hyde & Andrew Simpson (2015). Parallels Between Action‐Object Mapping and Word‐Object Mapping in Young Children. Cognitive Science 40 (1).
    Across a series of four experiments with 3- to 4-year-olds we demonstrate how cognitive mechanisms supporting noun learning extend to the mapping of actions to objects. In Experiment 1 the demonstration of a novel action led children to select a novel, rather than a familiar object. In Experiment 2 children exhibited long-term retention of novel action-object mappings and extended these actions to other category members. In Experiment 3 we showed that children formed an accurate sensorimotor record of the novel action. (...)
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  27.  15
    Marc Ettlinger, Amy S. Finn & Carla L. Hudson Kam (2011). The Effect of Sonority on Word Segmentation: Evidence for the Use of a Phonological Universal. Cognitive Science 36 (4):655-673.
    It has been well documented how language-specific cues may be used for word segmentation. Here, we investigate what role a language-independent phonological universal, the sonority sequencing principle (SSP), may also play. Participants were presented with an unsegmented speech stream with non-English word onsets that juxtaposed adherence to the SSP with transitional probabilities. Participants favored using the SSP in assessing word-hood, suggesting that the SSP represents a potentially powerful cue for word segmentation. To ensure the SSP influenced (...)
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  28.  11
    Gerlof J. Bouma & Petra Hendriks (2012). Partial Word Order Freezing in Dutch. Journal of Logic, Language and Information 21 (1):53-73.
    Dutch allows for variation as to whether the first position in the sentence is occupied by the subject or by some other constituent, such as the direct object. In particular situations, however, this commonly observed variation in word order is ‘frozen’ and only the subject appears in first position. We hypothesize that this partial freezing of word order in Dutch can be explained from the dependence of the speaker’s choice of word order on the hearer’s interpretation of (...)
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  29.  1
    Lawrence Phillips & Lisa Pearl (2015). The Utility of Cognitive Plausibility in Language Acquisition Modeling: Evidence From Word Segmentation. Cognitive Science 39 (8):1824-1854.
    The informativity of a computational model of language acquisition is directly related to how closely it approximates the actual acquisition task, sometimes referred to as the model's cognitive plausibility. We suggest that though every computational model necessarily idealizes the modeled task, an informative language acquisition model can aim to be cognitively plausible in multiple ways. We discuss these cognitive plausibility checkpoints generally and then apply them to a case study in word segmentation, investigating a promising Bayesian segmentation strategy. We (...)
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  30.  1
    Stanley Burris (1995). Polynomial Time Uniform Word Problems. Mathematical Logic Quarterly 41 (2):173-182.
    We have two polynomial time results for the uniform word problem for a quasivariety Q: The uniform word problem for Q can be solved in polynomial time iff one can find a certain congruence on finite partial algebras in polynomial time. Let Q* be the relational class determined by Q. If any universal Horn class between the universal closure S and the weak embedding closure S̄ of Q* is finitely axiomatizable then the uniform word problem for Q (...)
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  31.  1
    Daniel E. Cohen, Klaus Madlener & Friedrich Otto (1993). Seperating the Intrinsic Complexity and the Derivational Complexity of the Word Problem for Finitely Presented Groups. Mathematical Logic Quarterly 39 (1):143-157.
    A pseudo-natural algorithm for the word problem of a finitely presented group is an algorithm which not only tells us whether or not a word w equals 1 in the group but also gives a derivation of 1 from w when w equals 1. In [13], [14] Madlener and Otto show that, if we measure complexity of a primitive recursive algorithm by its level in the Grzegorczyk hierarchy, there are groups in which a pseudo-natural algorithm is arbitrarily more (...)
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  32.  2
    Séverine Fay, Michel Isingrini & Viviane Pouthas (2005). Does Priming with Awareness Reflect Explicit Contamination? An Approach with a Response-Time Measure in Word-Stem Completion. Consciousness and Cognition 14 (3):459-473.
    The present experiment investigates the involvement of awareness in functional dissociations between explicit and implicit tests. In the explicit condition, participants attempted to recall lexically or semantically studied words using word stems. In the implicit condition, they were instructed to complete each stem with the first word which came to mind. Subjective awareness was subsequently measured on an item-by-item basis. As voluntary retrieval strategies are known to be time consuming, the time taken to complete each stem was recorded. (...)
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  33.  27
    Norbert Corver & Henk C. van Riemsdijk (eds.) (1994). Studies of Scrambling: Movement and Non-Movement Approaches to Free Word-Order Phenomena. Mouton De Gruyter.
    ... the phenomenon of variable word order within a clause. Ross (), who was one of the first to discuss this phenomenon within the generative paradigm, ...
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  34.  18
    Susann Fischer (2010). Word-Order Change as a Source of Grammaticalisation. John Benjamins Pub. Company.
    1. Introduction -- 2. Different views on grammaticalisation and its relation to word-order -- 3. Historical overview of oblique subjects in Germanic and Romance -- 4. Historical overview of stylistic fronting in Germanic and Romance -- 5. Accounting for the differences and similarities between the languages under investigation -- 6. Explaining the changes: minimalism meets von Humboldt and Meillet -- References.
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  35.  6
    Simin Karimi (ed.) (2003). Word Order and Scrambling. Blackwell Pub..
    Word Order and Scrambling introduces readers to recent research into the linguistic phenomenon called scrambling and is a valuable contribution to the fields of ...
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  36.  17
    Eva Koktova (1999). Word-Order Based Grammar. Mouton De Gruyter.
    In this book, a new theory of grammar based on word order is proposed: a deep word order as the multipartioned communicative-information structure of the ...
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  37. Ildo Perondi, Fabrizio Zandonadi Catenassi & Gisele Soares Silva (2013). A centralidade da Palavra de Deus em Lucas 5,1-11 (The centrality of the Word od God in Luke 5,1-11) - DOI: 10.5752/P.2175-5841.2013v11n30p682. [REVIEW] Horizonte 11 (30):682-708.
    Pouca atenção foi dada pelos estudiosos para a função da Palavra de Deus no relato da pesca milagrosa em Lucas, tanto em nível literário, quanto teológico. Diante disso, o objetivo deste trabalho foi analisar a perícope de Lc 5,1-11, com enfoque na Palavra de Deus, proclamada em Jesus e por ele. A metodologia utilizada foi a análise e interpretação de textos, privilegiando o método histórico-crítico e os seus elementos essenciais, além do uso de outros métodos, baseados na ciência da linguagem. (...)
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  38. Larissa K. Samuelson, Sarah C. Kucker & John P. Spencer (2016). Moving Word Learning to a Novel Space: A Dynamic Systems View of Referent Selection and Retention. Cognitive Science 40 (4):n/a-n/a.
    Theories of cognitive development must address both the issue of how children bring their knowledge to bear on behavior in-the-moment, and how knowledge changes over time. We argue that seeking answers to these questions requires an appreciation of the dynamic nature of the developing system in its full, reciprocal complexity. We illustrate this dynamic complexity with results from two lines of research on early word learning. The first demonstrates how the child's active engagement with objects and people supports referent (...)
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  39.  42
    Jae Jung Song (2012). Word Order. Cambridge University Press.
    A one-stop resource on the current developments in word order research, this comprehensive survey provides an up-to-date, critical overview of this widely debated topic, exploring and evaluating research carried out in four major ...
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  40. John A. Hawkins (1983). Word Order Universals. Academic Press.
  41.  4
    Glyn W. Humphreys & Lindsay J. Evett (1985). Are There Independent Lexical and Nonlexical Routes in Word Processing? An Evaluation of the Dual-Route Theory of Reading. Behavioral and Brain Sciences 8 (4):689-705.
  42.  7
    Mortimer Mishkin & Donald G. Forgays (1952). Word Recognition as a Function of Retinal Locus. Journal of Experimental Psychology 43 (1):43.
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  43.  2
    James S. Magnuson, James A. Dixon, Michael K. Tanenhaus & Richard N. Aslin (2007). The Dynamics of Lexical Competition During Spoken Word Recognition. Cognitive Science 31 (1):133-156.
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  44.  17
    Jennifer Culbertson & Paul Smolensky (2012). A Bayesian Model of Biases in Artificial Language Learning: The Case of a Word‐Order Universal. Cognitive Science 36 (8):1468-1498.
  45.  6
    Laurence J. Severance & Frederick N. Dyer (1973). Failure of Subliminal Word Presentations to Generate Interference to Color Naming. Journal of Experimental Psychology 101 (1):186.
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  46.  68
    Andy Clark (2005). Word, Niche and Super-Niche: How Language Makes Minds Matter More. Theoria 20 (54):255-268.
    How does language (spoken or written) impact thought? One useful way to approach this important but elusive question may be to consider language itself as a cognition-enhancing animal-built structure. To take this perspective is to view language as a kind of self-constructed cognitive niche. These self-constructed cognitive niches play, I suggest, three distinct but deeply interlocking roles in human thought and reason. Working together, these three interlocking routines radically transform the human mind, and mark a genuine discontinuity in the space (...)
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  47.  12
    Lynne C. Nygaard, Debora S. Herold & Laura L. Namy (2009). The Semantics of Prosody: Acoustic and Perceptual Evidence of Prosodic Correlates to Word Meaning. Cognitive Science 33 (1):127-146.
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  48.  17
    Emily Mather & Kim Plunkett (2012). The Role of Novelty in Early Word Learning. Cognitive Science 36 (7):1157-1177.
    What mechanism implements the mutual exclusivity bias to map novel labels to objects without names? Prominent theoretical accounts of mutual exclusivity (e.g., Markman, 1989, 1990) propose that infants are guided by their knowledge of object names. However, the mutual exclusivity constraint could be implemented via monitoring of object novelty (see Merriman, Marazita, & Jarvis, 1995). We sought to discriminate between these contrasting explanations across two preferential looking experiments with 22-month-olds. In Experiment 1, infants viewed three objects: one name-known, two name-unknown. (...)
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  49. Steven J. Hasse & Gary D. Fisk (2001). Confidence in Word Detection Predicts Word Identification: Implications for an Unconscious Perception Paradigm. American Journal of Psychology 114 (3):439-468.
  50.  29
    Sid Kouider & Emmanuel Dupoux (2001). A Functional Disconnection Between Spoken and Visual Word Recognition: Evidence From Unconscious Priming. Cognition 82 (1):35- 49.
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