1,721,017 research outputs found
The puzzle of ambiguity
No full textTom Wasow, Amy Perfors and David Beaverhttp://trove.nla.gov.au/work/1110370
How do people learn from negative evidence? Non-monotonic generalizations and sampling assumptions in inductive reasoning
No full textAbstract not availableWouter Voorspoels, Daniel J. Navarro, Amy Perfors, Keith Ransom, Gert Storm
Poverty of the stimulus? A rational approach
Full text linkThe Poverty of the Stimulus (PoS) argument holds that children do not receive enough evidence to infer the exis-tence of core aspects of language, such as the dependence of linguistic rules on hierarchical phrase structure. We reevaluate one version of this argument with a Bayesian model of grammar induction, and show that a rational learner without any initial language-speci¯c biases could learn this dependency given typical child-directed input. This choice enables the learner to master aspects of syn-tax, such as the auxiliary fronting rule in interrogative formation, even without having heard directly relevant data (e.g., interrogatives containing an auxiliary in a relative clause in the subject NP).Amy Perfors, Joshua B. Tenenbaum and Terry Regie
People are sensitive to hypothesis sparsity during category discrimination
Full text linkPrevious work has shown that the information value of requests can be manipulated by controlling the sparsity of hypotheses, the degree to which category members are rare or common in the domain under consideration when making those requests. However, the degree to which people are sensitive to expected information value is unknown. This study examined a binary sorting task where sparsity differed across conditions. In contrast to previous work using hypotheses representable as visual areas, the stimuli in this study defined hypotheses in an abstract similarity space over geometric shapes. Participants could request labels for either category members or non-members. While both request types were used in all conditions, most often evenly, the proportion of participants showing a preference for one type of request was strongly impacted by the information value of that request type. A small tendency to prefer requests from the designated target category was also observed.Steven Langsford, Andrew T. Hendrickson, Amy Perfors, Daniel J. Navarr
Leaping to Conclusions: Why Premise Relevance Affects Argument Strength
No full textEveryday reasoning requires more evidence than raw data alone can provide. We explore the idea that people can go beyond this data by reasoning about how the data was sampled. This idea is investigated through an examination of premise non-monotonicity, in which adding premises to a category-based argument weakens rather than strengthens it. Relevance theories explain this phenomenon in terms of people’s sensitivity to the relationships among premise items. We show that a Bayesian model of category-based induction taking premise sampling assumptions and cate- gory similarity into account complements such theories and yields two important predictions: First, that sensitivity to premise relationships can be violated by inducing a weak sampling assumption; and second, that premise monotonici ty should be restored as a result. We test these predictions with an experiment that manipulates people’s assumptions in this regard, showing that people draw qualitatively different conclusions in each case.Keith J. Ransom, Amy Perfors, Daniel J. Navarr
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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