130,402 research outputs found
Poaching is more than an enforcement problem
No full textToday record levels of funding are being invested in enforcement and anti-poaching measures to tackle the “war on poaching,” but many species are on the path to extinction. In our view, intensifying enforcement effort is crucial, but will ultimately prove an inadequate long-term strategy with which to conserve high-value species. This is because: regulatory approaches are being overwhelmed by the drivers of poaching and trade, financial incentives for poaching are increasing due to rising prices and growing relative poverty between areas of supply and centres of demand, and aggressive enforcement of trade controls, in particular bans, can increase profits and lead to the involvement of organised criminals with the capacity to operate even under increased enforcement effort. With prices for high-value wildlife rising, we argue that interventions need to go beyond regulation and that new and bold strategies are needed urgently. In the immediate future, we should incentivise and build capacity within local communities to conserve wildlife. In the medium term, we should drive prices down by reexamining sustainable off-take mechanisms such as regulated trade, ranching and wildlife farming, using economic levers such as taxation to fund conservation efforts, and in the long-term reduce demand through social marketing programs
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
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
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
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
Scholarly Communication and Publishing Lunch and Learn Talk #11: The ULS Open Access Author Fee Fund
No full textAt the May 2014 talk, you will learn about the ULS Open Access Author Fee Fund--what it is, why we do it, how it works, and how the program is going so far
The R&D Tax Incentives
No full textThis article sets out some background information and reflections of the author on the R&D tax incentive schemes included in the Common Corporate Tax Base (CCTB) Proposal. In particular the author analyzes the stimulus to private R&D through ad hoc tax incentives included in the CCTB Proposal and dives into the actual provisions included in the Proposal highlighting the most relevant issues connected with their design and interpretation. Moreover, the author explores the interaction between the CCTB Proposal and the granting by Member States of domestic R&D tax incentives
Understanding Urban Demand for Wild Meat in Vietnam: Implications for Conservation Actions
No full textVietnam is a significant consumer of wildlife, particularly wild meat, in urban restaurant settings. To meet this demand, poaching of wildlife is widespread, threatening regional and international biodiversity. Previous interventions to tackle illegal and potentially unsustainable consumption of wild meat in Vietnam have generally focused on limiting supply. While critical, they have been impeded by a lack of resources, the presence of increasingly organised criminal networks and corruption. Attention is, therefore, turning to the consumer, but a paucity of research investigating consumer demand for wild meat will impede the creation of effective consumer-centred interventions. Here we used a mixed-methods research approach comprising a hypothetical choice modelling survey and qualitative interviews to explore the drivers of wild meat consumption and consumer preferences among residents of Ho Chi Minh City, Vietnam. Our findings indicate that demand for wild meat is heterogeneous and highly context specific. Wild-sourced, rare, and expensive wild meat-types are eaten by those situated towards the top of the societal hierarchy to convey wealth and status and are commonly consumed in lucrative business contexts. Cheaper, legal and farmed substitutes for wild-sourced meats are also consumed, but typically in more casual consumption or social drinking settings. We explore the implications of our results for current conservation interventions in Vietnam that attempt to tackle illegal and potentially unsustainable trade in and consumption of wild meat and detail how our research informs future consumer-centric conservation actions
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