14,495 research outputs found

    Work, version, text and scriptum: high medieval manuscript terminology in the aftermath of the new philology

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    This article reviews the terminological framework to describe manuscripts. The Lachmannian terminology allows scholars to classify manuscripts as versions or variants of a work on a purely textual basis, but lacks a rigid designator to indicate a (part of a) manuscript as a unit of text and material considerations. Conversely, scholars who adopt Dagenais’ solution to renounce the work and concentrate on the material scriptum gain a rigid designator, but threaten to lose the ability to classify manuscripts at all. Proceeding from a case study, the article argues that the twelfth-century view of a work’s ontological status enables medievalists to keep classifying their scripta on both textual and material grounds. It explores the possibility of using Dagenais’ scriptum as the foundation for a Neo-Lachmannian terminological framework that allows scholars to study manuscript variance and materiality without losing the ability to classify them

    Determination of gross production curves for grassland from exploitation data

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    Who students interact with? A social network analysis perspective on the use of Twitter in language learning

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    This paper reports student interaction patterns and self-reported results of using Twitter microblogging environment. The study employs longitudinal probabilistic social network analysis (SNA) to identify the patterns and trends of network dynamics. It is building on earlier works that explore associations of student achievement records with the observed network measures. It integrates gender as an additional variable and reports some relation with interaction patterns. Additionally, the paper reports the results of a questionnaire that enables further discussion on the communication patterns

    A Separable Model for Dynamic Networks

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    Models of dynamic networks --- networks that evolve over time --- have manifold applications. We develop a discrete-time generative model for social network evolution that inherits the richness and flexibility of the class of exponential-family random graph models. The model --- a Separable Temporal ERGM (STERGM) --- facilitates separable modeling of the tie duration distributions and the structural dynamics of tie formation. We develop likelihood-based inference for the model, and provide computational algorithms for maximum likelihood estimation. We illustrate the interpretability of the model in analyzing a longitudinal network of friendship ties within a school.Comment: 28 pages (including a 4-page appendix); a substantial rewrite, with many corrections, changes in terminology, and a different analysis for the exampl

    Entrepreneurship in the Netherlands: Opportunities and threats to nascent entrepreneurship

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    Derde editie van ‘Entrepreneurship in the Netherlands’. In drie bijdragen wordt ingegaan op de fase voor de start van een nieuw bedrijf. De rol van prestarters in de Nederlandse economie wordt beschreven. Het stimuleringsbeleid ten aanzien van prestarters komt aan de orde, met bijzondere aandacht voor de stimulering van ondernemerschap in het onderwijs. Tot slot wordt een vergelijking gemaakt tussen de ontwikkeling van prestarters in de Verenigde Staten en die in Nederland. De verschillen tussen Nederland en de VS worden uitgelegd in de context van verschillen tussen de nationale, culturele, politieke en economische systemen in de twee landen.

    Infants segment words from songs - an EEG study

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    Children’s songs are omnipresent and highly attractive stimuli in infants’ input. Previous work suggests that infants process linguistic–phonetic information from simplified sung melodies. The present study investigated whether infants learn words from ecologically valid children’s songs. Testing 40 Dutch-learning 10-month-olds in a familiarization-then-test electroencephalography (EEG) paradigm, this study asked whether infants can segment repeated target words embedded in songs during familiarization and subsequently recognize those words in continuous speech in the test phase. To replicate previous speech work and compare segmentation across modalities, infants participated in both song and speech sessions. Results showed a positive event-related potential (ERP) familiarity effect to the final compared to the first target occurrences during both song and speech familiarization. No evidence was found for word recognition in the test phase following either song or speech. Comparisons across the stimuli of the present and a comparable previous study suggested that acoustic prominence and speech rate may have contributed to the polarity of the ERP familiarity effect and its absence in the test phase. Overall, the present study provides evidence that 10-month-old infants can segment words embedded in songs, and it raises questions about the acoustic and other factors that enable or hinder infant word segmentation from songs and speech

    Entrepreneurship in the Netherlands: Ambitious entrepreneurs: the driving force for the next millennium

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    Studie naar de dynamiek van jonge bedrijven en snelgroeiende bedrijven in Nederland, Denemarken, het Verenigd Koninkrijk, de Verenigde Staten en Zweden. In Nederland zijn er relatief weinig bedrijven met hoge werkgelegenheidsgroei. In tegenstelling tot andere landen ontwikkelt de Nederlandse overheid wel beleid om snelgroeiende bedrijven te ondersteunen.

    Maximum likelihood estimation for social network dynamics

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    A model for network panel data is discussed, based on the assumption that the observed data are discrete observations of a continuous-time Markov process on the space of all directed graphs on a given node set, in which changes in tie variables are independent conditional on the current graph. The model for tie changes is parametric and designed for applications to social network analysis, where the network dynamics can be interpreted as being generated by choices made by the social actors represented by the nodes of the graph. An algorithm for calculating the Maximum Likelihood estimator is presented, based on data augmentation and stochastic approximation. An application to an evolving friendship network is given and a small simulation study is presented which suggests that for small data sets the Maximum Likelihood estimator is more efficient than the earlier proposed Method of Moments estimator.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS313 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org
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