305,654 research outputs found
Rapid recovery of accessibility: Primary research in support of a connectionist model of person memory
No full textTwo experiments are described testing whether priming a construct at one Point of time makes it easier to again increase the accessibility of that construct at a later point in time, even after the accessibility has returned to baseline. This hypothesis, termed the rapid recovery of accessibility, was generated from Smith and DeCoster\u27s (1998) connectionist model of person memory. Other theories of accessibility have difficulty accounting for such an effect, so these experiments constitute an appropriate test of Smith and DeCoster\u27s Model. Experiment 1, using attitude accessibility, failed to find evidence of the rapid recovery of accessibility after either a one-week or six-week delay. Experiment 2, however, found that trait prunes were more effective if the traits had also been primed six-weeks earlier
Microsimulation of indirect taxes
No full textThe goal of this paper is to simulate a tax shift from labour to consumption and perform a distributional analysis of the reform. Microsimulation programs are often uniquely focussed on the personal income tax system and on social security contributions and benefits. However, against a political background where income taxes are under increased pressure and alternative, less distortive forms of taxation come under consideration, microsimulation models enriched with expenditure data and consumption tax structures could play an important role in sharpening the (distributional) picture of such systemic changes. The current paper discusses an algorithm for this enrichment - mainly with VAT, excises and other consumption taxes - within the context of the EUROMOD-framework and applies the obtained program to the simulation of a decrease of social security contributions compensated by a rise in standard VAT rate to maintain government budget neutrality for four EU countries. The measure is found to have a (first order) regressive effect, pointing to the fact that keeping redistribution constant would require the remaining post-reform income taxation to become more progressive.
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe 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
Dispelling the Myths Behind First-author Citation Counts
No full textWe 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
Author, publisher and bookseller : a tripartite synergy in Nigerian book industry
No full textThis work is about the roles of Author, Publisher and Bookseller in Book development in
Nigeria. The paper started by delving into the history of Book Publishing in Nigeria after
which it proceeded by defining who an author, a publisher, and a bookseller is and
expatiated on the indispensable roles of these key actors in Nigerian Book Industry and in
the emerging Information Society. Furthermore, the various constraints to book
development were identified while the paper advised on how the Book Industry can be
further promoted in Nigeria. However, the paper concluded and made recommendations
on how the Book sector can help in enhancing scholarship in the country
[Report to Chief J. E. Curry, by an unknown author #2]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
[Report to Chief J. E. Curry, by an unknown author #1]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
Mining e-mail content for author identification forensics
No full textWe describe an investigation into e-mail content mining for author identification, or authorship attribution, for the purpose of forensic investigation. We focus our discussion on the ability to discriminate between authors for the case of both aggregated e-mail topics as well as across different email topics. An extended set of e-mail document features including structural characteristics and linguistic patterns were derived and, together with a Support Vector Machine learning algorithm, were used for mining the e-mail content. Experiments using a number of e-mail documents generated by different authors on a set of topics gave promising results for both aggregated and multi-topic author categorisation
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