scholarly journals Inside Job or Deep Impact? Extramural Citations and the Influence of Economic Scholarship

2020 ◽  
Vol 58 (1) ◽  
pp. 3-52 ◽  
Author(s):  
Josh Angrist ◽  
Pierre Azoulay ◽  
Glenn Ellison ◽  
Ryan Hill ◽  
Susan Feng Lu
Keyword(s):  
Social Sciences ◽  
Machine Learning ◽  
Economic Theory ◽  
Empirical Work ◽  
Economic Research ◽  
Deep Impact ◽  
General Scientific ◽  
Economics Journals ◽  
Scientific Value ◽  
Field Influence

Does academic economic research produce material of general scientific value, or do academic economists write only for peers? Is economics scholarship uniquely insular? We address these questions by quantifying interactions between economics and other disciplines. Changes in the influence of economic scholarship are measured here by the frequency with which other disciplines cite papers in economics journals. We document a clear rise in the extramural influence of economic research, while also showing that economics is increasingly likely to reference other social sciences. A breakdown of extramural citations by economics fields shows broad field influence. Differentiating between theoretical and empirical papers classified using machine learning, we see that much of the rise in economics’ extramural influence reflects growth in citations to empirical work. This growth parallels an increase in the share of empirical cites within economics. At the same time, some disciplines that primarily cite economic theory have also recently increased citations of economics scholarship. ( JEL A11, A14)

Modern Economic Theory: The Main Tendencies

2007 ◽  
pp. 35-54 ◽  
Author(s):  
A. Libman
Keyword(s):  
Social Sciences ◽  
Economic Theory ◽  
Empirical Research ◽  
Scientific Community ◽  
Economic Research ◽  
Economic Science ◽  
Mainstream Economics ◽  
Advantages And Disadvantages ◽  
Modern Economic ◽  
Methodological Approaches

The paper presents a survey of the main fields of theoretical and empirical research in economics and social sciences. It offers two classifications of economic research based on methodology and segments of scientific community. Advantages and disadvantages of different methodological approaches and standards of communication are considered. The article also discusses the main directions of evolution of mainstream economics, as well as empirical and experimental turn in the modern economic science.

scholarly journals Economic Research Evolves: Fields and Styles

2017 ◽  
Vol 107 (5) ◽  
pp. 293-297 ◽  
Author(s):  
Joshua Angrist ◽  
Pierre Azoulay ◽  
Glenn Ellison ◽  
Ryan Hill ◽  
Susan Feng Lu
Keyword(s):  
Machine Learning ◽  
Field Distribution ◽  
Empirical Work ◽  
Theoretical Work ◽  
Economic Research ◽  
Regression Analyses ◽  
Economics Research

We examine the evolution of economics research using a machine-learning-based classification of publications into fields and styles. The changing field distribution of publications would not seem to favor empirical papers. But economics' empirical shift is a within-field phenomenon; even fields that traditionally emphasize theory have gotten more empirical. Empirical work has also come to be more cited than theoretical work. The citation shift is sharpened when citations are weighted by journal importance. Regression analyses of citations per paper show empirical publications reaching citation parity with theoretical publications around 2000. Within fields and journals, however, empirical work is now cited more.

scholarly journals An Empirical Comparison of Bias Reduction Methods on Real-World Problems in High-Stakes Policy Settings

2021 ◽  
Vol 23 (1) ◽  
pp. 69-85
Author(s):  
Hemank Lamba ◽  
Kit T. Rodolfa ◽  
Rayid Ghani
Keyword(s):  
Machine Learning ◽  
Real World ◽  
Empirical Work ◽  
Bias Reduction ◽  
Research Community ◽  
High Stakes ◽  
Social Good ◽  
Social Service Delivery ◽  
Reduction Methods ◽  
Applications Of Machine Learning

Applications of machine learning (ML) to high-stakes policy settings - such as education, criminal justice, healthcare, and social service delivery - have grown rapidly in recent years, sparking important conversations about how to ensure fair outcomes from these systems. The machine learning research community has responded to this challenge with a wide array of proposed fairness-enhancing strategies for ML models, but despite the large number of methods that have been developed, little empirical work exists evaluating these methods in real-world settings. Here, we seek to fill this research gap by investigating the performance of several methods that operate at different points in the ML pipeline across four real-world public policy and social good problems. Across these problems, we find a wide degree of variability and inconsistency in the ability of many of these methods to improve model fairness, but postprocessing by choosing group-specific score thresholds consistently removes disparities, with important implications for both the ML research community and practitioners deploying machine learning to inform consequential policy decisions.

scholarly journals Intelligent Predicting Learning Disabilities in School Going Children using Fuzzy Logic K Mean Clustering in Machine Learning.

2019 ◽  
Vol 8 (4) ◽  
pp. 1694-1698
Keyword(s):  
Social Sciences ◽  
Machine Learning ◽  
Decision Making ◽  
Learning Disabilities ◽  
Fuzzy Logic ◽  
Side Effects ◽  
Early Analysis ◽  
Comprehensive Investigation ◽  
Engineering Statistics ◽  
Decision Making System

Learning disabilities (LD) is turning into a major issue in various nations around the globe which can even contrarily influence human common advancement. The undertaking of this work is to help the specialized programme network in their task to be with the standard. The underlying section of the paper gives a comprehensive investigation of the distinctive components of diagnosing learning disabilities. Despite the fact that LD can be analysed early - before 5 years of age, most youngsters were not determined to have LD until the age of nine on account of its unpredictable side effects and unclear indication in children disorder issue. Fuzzy logic K-means clustering has inspired a tremendous transformation in Machine learning and can take and able to resolve a variation of problems. This paper is the elaboration on the strategy for utilizing this mix to encourage the early analysis of LD. Since Fuzzy Logic clustering in Machine Learning is generally considered and connected in different areas of science, we invite all the related analysts from the fields of computer science, engineering, statistics, social sciences, healthcare, and so on, etc. The result of the paper demonstrates that the previously mentioned methodology can possibly be the potential of the supporting decision-making system in LD investigating and diagnosing.

scholarly journals ЛИНГВОПРАГМАТИЧЕСКИЙ АСПЕКТ РОЖДЕСТВЕНСКИХ ОБРАЩЕНИЙ ФИЛИППА VI

2020 ◽  
Author(s):  
Irina Selivanova
Keyword(s):  
Institutional Discourse ◽  
Peaceful Coexistence ◽  
Spanish Society ◽  
Scientific Methods ◽  
Discursive Analysis ◽  
Communicative Strategies ◽  
Head Of State ◽  
General Scientific ◽  
Universal Values ◽  
Scientific Value

Введение. Изучены стратегии и тактики речевой манипуляции в рождественских обращениях испанского монарха Филиппа VI с 2014 по 2019 гг. Материал и методы. Исследование проведено на материале шести рождественских посланий Филиппа VI, опубликованных на официальном сайте Королевского дома Испании. В работе применяются как общенаучные методы (описание, наблюдение, обобщение и систематизация), так и методы лингвистического анализа (лингвоидеологическая интерпретация, контент-анализ, дискурсивный анализ). Результаты и обсуждение. Рождественская речь анализируется в контексте политической риторики как нацеленный на публичное воздействие акт представительской коммуникации. Описываются конститутивные характеристики и коммуникативные детерминативы рождественских посланий Филиппа VI с 2014 по 2019 г. с учетом современного политического контекста Испании. Особое внимание уделяется используемым стратегиям и тактикам речевой манипуляции, обеспечивающим акт торжественного красноречия, а также центральным образам прошлого и настоящего, адресанта и адресата (общества), определяющим концептуальное пространство рождественского обращения. Научная новизна работы заключается не только в анализе коммуникативного и образного потенциала посланий монарха, но и в описании характерных признаков данного вида публичного выступления. Заключение. Рождественское обращение монарха представляет собой типичный пример направленного на воспитание определенных качеств торжественного красноречия. При этом глава государства выступает значимой общественной фигурой, обладающей правом не только толковать факты и события действительности (с целью сохранения единства нации и стабильности государства), но и обсуждать нравственные проблемы, основываясь на общечеловеческих ценностях как духовных скрепах социума. Рождественские послания Филиппа VI полностью соответствуют требованиям торжественного публичного выступления как особого коммуникативного события и характеризуются традиционным набором образов (адресата и адресанта), транслируемых ценностей (демократических и общечеловеческих) и стратегий речевого воздействия (стратегия самопрезентации, информационно-интерпретационная стратегия, аргументативная стратегия, агитационная стратегия, стратегия формирования эмоционального настроя адресата), подчеркивающих роль монарха как единственного хранителя и гаранта коллективной идентичности, процветания и стабильности государства.Introduction. The article deals with the communicative strategies and tactics of linguistic manipulation used in the six Christmas messages issued by the Spanish King Felipe VI from 2014 to 2019. Material and methods. The analysis of Felipe VI’s Christmas messages, published on the official website of the Royal House, was based on general scientific methods (description, observation, generalization, and systematization) as well as linguistic analysis methods (linguistic interpretation, content analysis, discursive analysis). Results and discussion. This article describes some features of Felipe VI’s Christmas messages (from 2014 to 2019), taking into account the current political situation of Spain. These texts are considered a ritual genre of institutional discourse and are analyzed in the context of political rhetoric. The paper is aimed to highlight how the messages are used with an ideological purpose to strengthen the image of the monarchy and to convince people of the necessity for peaceful coexistence, respect for the law, and national pride. The article also focuses on the images of the past, the present, the addressee (Spanish society) and the country. The scientific value of this paper is in describing the most popular communicative strategies and tactics of linguistic manipulation used by the Spanish King. Conclusion. The monarch’s Christmas messages can be considered a typical example of ceremonial eloquence in which the Head of State acts as a significant public figure, not only interpreting facts and events in order to preserve the unity of the nation and stability of the country, but also discussing moral issues based on universal values. It was revealed that Felipe VI tends to use a set of communicative strategies and tactics in order to underline the importance of peaceful coexistence in Spain and to emphasize his role as the only guarantor of stability, unity, prosperity and social justice.

Maximizing, Moralizing, and Dramatizing

2012 ◽  
Author(s):  
Alan Ryan
Keyword(s):  
Social Sciences ◽  
Economic Theory ◽  
Social Interaction ◽  
Social Life ◽  
Voting Behavior ◽  
Karl Popper ◽  
Crucial Element ◽  
The Social ◽  
Theory Of Democracy

This chapter describes a “dramatistic,” “dramatic,” or “dramaturgical” approach to the study of social interaction. It asks whether the dramaturgical model insists on the theatricality of social life merely in the sense of insisting that people fill roles just as persons act parts in a play. This is the question of whether the crucial element in the dramaturgical picture is that cluster of insights that goes under the general heading of “role distance.” The chapter considers the peculiarities of rational explanation and about the role of reconstructions of “the thing to do” other than the role of explaining an action or series of actions by focusing on voting behavior in the terms proposed by Anthony Downs's An Economic Theory of Democracy. It also examines some recent accounts of the phenomenon of suicide, along with the rationality principle, which Karl Popper calls “false but indispensable” to the social sciences.

From Relevant to in Demand?

2018 ◽  
Vol 2018 (3) ◽  
pp. 3-22
Author(s):  
Andrey Shastitko
Keyword(s):  
Economic Theory ◽  
Economic History ◽  
Capital Accumulation ◽  
Karl Marx ◽  
Subsequent Development ◽  
Fundamental Question ◽  
Economic Research ◽  
Institutional Economic ◽  
Production Relations ◽  
Key Aspects

The article offers a survey of some of the ideas of Karl Marx in the context of the subsequent development of the new institutional economic theory in the 20th - early 21st centuries. It discusses various aspects of the unity of the historical and the logical in Marx’s Capital in the light of various ways of combining the historical and the theoretical in economic research, including a new economic history. The article considers the issues of the linkages between the problems of import and transplantation of institutes and the export of production relations, as well as the interaction of institutes and technologies, but in the context of the contradiction between productive forces and production relations, and possible parallels between the initial ideas of transaction costs and costs of circulation in the second volume of Marx’s Capital. It discusses the fundamental question of the absolute law of capital accumulation in the context of two key aspects of institutes - coordination and distribution.

scholarly journals RESPONSE FUNCTIONS TO CRITICAL SHOCKS IN SOCIAL SCIENCES: AN EMPIRICAL AND NUMERICAL STUDY

2004 ◽  
Vol 15 (06) ◽  
pp. 809-834 ◽  
Author(s):  
B. M. ROEHNER ◽  
D. SORNETTE ◽  
J. V. ANDERSEN
Keyword(s):  
Social Sciences ◽  
Numerical Study ◽  
Empirical Work ◽  
Natural Sciences ◽  
Large Variability ◽  
Future Evolution ◽  
Damage Spreading ◽  
Exogenous Shocks ◽  
The Social ◽  
The Difference

We show that, provided one focuses on properly selected episodes, one can apply to the social sciences the same observational strategy that has proved successful in natural sciences such as astrophysics or geodynamics. For instance, in order to probe the cohesion of a society, one can, in different countries, study the reactions to some huge and sudden exogenous shocks, which we call Dirac shocks. This approach naturally leads to the notion of structural (as opposed or complementary to temporal) forecast. Although structural predictions are by far the most common way to test theories in the natural sciences, they have been much less used in the social sciences. The Dirac shock approach opens the way to testing structural predictions in the social sciences. The examples reported here suggest that critical events are able to reveal pre-existing "cracks" because they probe the social cohesion which is an indicator and predictor of future evolution of the system, and in some cases they foreshadow a bifurcation. We complement our empirical work with numerical simulations of the response function ("damage spreading") to Dirac shocks in the Sznajd model of consensus build-up. We quantify the slow relaxation of the difference between perturbed and unperturbed systems, the conditions under which the consensus is modified by the shock and the large variability from one realization to another.

Economic studies: history, theory, methodology

2020 ◽  
Author(s):  
Vladimir Balikoev
Keyword(s):  
Economic Theory ◽  
Financial Management ◽  
Dialectical Materialism ◽  
Economic Research ◽  
Economic Activities ◽  
Perspective Theory ◽  
Analysis And Synthesis ◽  
Methodological Problems ◽  
Accessible Form ◽  
Economic Studies

It analyzes methodological problems of contemporary economic theory and concrete economic disciplines. In a simple and accessible form set out in historical perspective theory and methodology of economic research in a variety of economic doctrines from mercantilism to contemporary neoliberalism. Much attention is paid to the national identity of economic theory in the methodological aspect. In detail and with specific examples, discusses the methodology of dialectics and dialectical materialism, the combination of historical and logical, analysis and synthesis, induction and deduction, etc., as well as their tools of research — a scientific theory, concept, paradigm, principle, Maxim. Similar to the analysis in the example are exposed to methodologies and tools for economic studies analysis of economic activities, banking, statistics, accounting, and financial management. Addressed to students, undergraduates, graduate students, teachers and anyone interested in research methodology.

scholarly journals Big data need big theory too

2016 ◽  
Vol 374 (2080) ◽  
pp. 20160153 ◽  
Author(s):  
Peter V. Coveney ◽  
Edward R. Dougherty ◽  
Roger R. Highfield
Keyword(s):  
Social Sciences ◽  
Machine Learning ◽  
Big Data ◽  
Data Analytics ◽  
Conceptual Knowledge ◽  
Structural Characteristics ◽  
Multiscale Modelling ◽  
Neural Nets ◽  
Data Driven ◽  
Scientific Methods

The current interest in big data, machine learning and data analytics has generated the widespread impression that such methods are capable of solving most problems without the need for conventional scientific methods of inquiry. Interest in these methods is intensifying, accelerated by the ease with which digitized data can be acquired in virtually all fields of endeavour, from science, healthcare and cybersecurity to economics, social sciences and the humanities. In multiscale modelling, machine learning appears to provide a shortcut to reveal correlations of arbitrary complexity between processes at the atomic, molecular, meso- and macroscales. Here, we point out the weaknesses of pure big data approaches with particular focus on biology and medicine, which fail to provide conceptual accounts for the processes to which they are applied. No matter their ‘depth’ and the sophistication of data-driven methods, such as artificial neural nets, in the end they merely fit curves to existing data. Not only do these methods invariably require far larger quantities of data than anticipated by big data aficionados in order to produce statistically reliable results, but they can also fail in circumstances beyond the range of the data used to train them because they are not designed to model the structural characteristics of the underlying system. We argue that it is vital to use theory as a guide to experimental design for maximal efficiency of data collection and to produce reliable predictive models and conceptual knowledge. Rather than continuing to fund, pursue and promote ‘blind’ big data projects with massive budgets, we call for more funding to be allocated to the elucidation of the multiscale and stochastic processes controlling the behaviour of complex systems, including those of life, medicine and healthcare. This article is part of the themed issue ‘Multiscale modelling at the physics–chemistry–biology interface’.

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