1,720,963 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Economic Equilibrium Model for Pollution Management and Resource Generation in a District: A Block-Level Approach
Get PDFThis paper develops an economic equilibrium model for pollution management and resource generation within a district, segmented into blocks. The model uses quadratic equations to derive equilibrium conditions at both block and district levels. The analysis incorporates principles from Keynesian, welfare, and environmental economics. The model is solved step by step, yielding collective equilibrium conditions consistent with global environmental commitments
The Economic Implications of AI-Driven Automation: A Dynamic General Equilibrium Analysis
No full textThis paper develops a dynamic general equilibrium (DGE) model to assess the impact of AI-driven automation on labor and capital allocation in an economy. The model considers the endogenous response of firms to task automation and labor substitution, showing how the increasing use of AI affects total output (GDP), wages, and capital returns. By introducing task complementarity and dynamic capital accumulation, the paper explores how automation impacts labor dynamics and capital accumulation. Key results show that while AI enhances productivity and GDP, it can also reduce wages
and increase income inequality, with long-run effects that depend on the elasticity of
substitution between labor and capital
A Quantum-Inspired Economic Equilibrium Model: Incorporating Uncertainty in Price and Money Flow Dynamics
Get PDFThis paper presents a quantum-inspired economic equilibrium model that incorporates fundamental uncertainty in market dynamics. Drawing upon the analogy between quantum mechanics and economic behavior, the model defines an uncertainty constant, σ, which limits the precision with which both price and money flow can be simultaneously predicted. The model investigates the dynamics of price and money f low as they asymptotically approach equilibrium, constrained by the uncertainty principle ∆P · ∆M ≥ σ. Solutions for price and money f low are derived, and the behavior of the system as it reaches equilibrium is analyzed, offering a novel perspective on how markets behave in the presence of irreducible uncertainty
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe 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
The Economic Implications of AI-Driven Automation: A Dynamic General Equilibrium Analysis
Get PDFThis paper develops a dynamic general equilibrium (DGE) model to assess the impact of AI-driven automation on labor and capital allocation in an economy. The model considers the endogenous response of firms to task automation and labor substitution, showing how the increasing use of AI affects total output (GDP), wages, and capital returns. By introducing task complementarity and dynamic capital accumulation, the paper explores how automation impacts labor dynamics and capital accumulation. Key results show that while AI enhances productivity and GDP, it can also reduce wages
and increase income inequality, with long-run effects that depend on the elasticity of
substitution between labor and capital
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