Relevant bibliographies by topics / Social Sciences Mathematical Methods

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Social Sciences Mathematical Methods'

Author: Grafiati
Published: 7 September 2023

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Journal articles on the topic "Social Sciences Mathematical Methods"

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Mutanen, Arto. "Constructive Methods in Economics." Synthesis philosophica 34, no. 1 (2019): 45–57. http://dx.doi.org/10.21464/sp34104.

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Constructive methods and constructivity have been under extensive discussion in the philosophy of science. In mathematics and experimental sciences, constructive methods have a long tradition. From experimental sciences, constructive methods broadened to empirical sciences, as constructive empiricism demonstrates. For the last few decades, scientists from social sciences have been discussing social constructionism, which is a new direction in this multidimensional tradition of constructive methods. In economics, mathematical methods such as game theory are generally used. The mathematisation of science can be done in the spirit of the pedagogic-scientific mode or technocratic-scientific mode, which both are present in economics. Mathematical and other constructive methods may allow us to find out scientific understanding for particular phenomena. However, there is a real danger that the whole of science becomes technocratic. The question is not about constructions, but the whole aim of science – whether it is pedagogical or not.
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Johnson, Robert A., and David J. Bartholomew. "Guidebook 1: Mathematical Methods in Social Science." Journal of the American Statistical Association 80, no. 389 (March 1985): 236. http://dx.doi.org/10.2307/2288083.

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Ehrhardt, Matthias, Lucas Jódar Sánchez, and Rafael Jacinto Villanueva Micó. "Numerical methods and mathematical modelling in biology, medicine and social sciences." International Journal of Computer Mathematics 91, no. 2 (February 2014): 176–78. http://dx.doi.org/10.1080/00207160.2014.896653.

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Nemtsov, A. V., and N. A. Zorin. "Mathematical methods in psychiatric papers." Scientometrics 42, no. 2 (June 1998): 121–28. http://dx.doi.org/10.1007/bf02458352.

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Khamkhoeva, F., and Z. Khautieva. "MODERN PROBLEMS OF APPLYING MATHEMATICAL METHODS IN THE ASPECT OF ECONOMICS." National Association of Scientists 3, no. 74 (December 30, 2021): 69–72. http://dx.doi.org/10.31618/nas.2413-5291.2021.3.74.530.

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The penetration of the mathematical apparatus into the economy created the basis for the development of methods of economic analysis, econometrics, mathematical programming, economic statistics, etc. Today, the interpenetration of different branches of knowledge continues, in particular, the application of mathematical methods in the natural and social sciences and in the economic sphere. Among mathematical methods of data processing are polynomial, linear, quadratic, trigonometric, exponential and combined dependencies, differential and algebraic equations. The statistical processing of data from the evaluation of the structure and dynamics of the phenomenon has gone in the direction of correlation analysis and forecasting. The deep penetration of mathematics into specific sciences and the success achieved through a combination of methods from different branches of knowledge is described by many researchers. The possibilities of applying mathematics are increasingly being explored in areas of knowledge where phenomena are poorly structured and characterized by the high complexity of sociology, political science, management and economics. The article presents a retrospective analysis of the development of scientific and applied research concerning the process of mathematics of science and the possibilities of using mathematical methods in economics in particular. Problems and constraints encountered in applying mathematical methods in economic research have been identified. Measures have been identified to ensure the adequacy of the development of economic and mathematical models from the standpoint of approaches to their construction, the improvement of management processes and the improvement of the training of specialists in economic fields.
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Andersen, Heine. "Gender inequality and paradigms in the social sciences." Social Science Information 40, no. 2 (June 2001): 265–89. http://dx.doi.org/10.1177/053901801040002004.

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The article is based on a survey of 788 Danish researchers, mainly from the social sciences, and analyses differences between female and male researchers concerning cognitive styles and cognitive convictions. Sandra Harding's portrait of modern science as androcentric and characterized by a set of gender-related dualisms is taken as a point of departure, and the results by and large show gender differences which can be related to this picture. Male researchers give more importance to methodological ideals taken from natural science, objectivity, mathematical methods, rationality, universality and cumulative results, etc., than female researchers do. These differences are shown to be correlated with the degree of power orientation of research topics.
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Irina, Shchemeleva. "“I’m Applying Mathematical Methods to Social Sciences” : Norms in Disciplinary Writing and Methodological Paradigms." Journal of AsiaTEFL 18, no. 4 (December 31, 2021): 1176–94. http://dx.doi.org/10.18823/asiatefl.2021.18.4.7.1176.

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Sokolova, Tatiana D., and Liana A. Tukhvatulina. "Methodological Reductionism and the Idea of Progress in the Social Sciences and Humanities: An Internalist Perspective." Voprosy Filosofii, no. 11 (2022): 76–86. http://dx.doi.org/10.21146/0042-8744-2022-11-76-86.

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In this paper, we consider the internalistic foundations of progress in the social sciences and humanities. Our working hypothesis is that a linear (cumulative) understanding of progress in the humanities and social sciences expresses itself in a tendency towards methodological reductionism (naturalization within episte­mology of social sciences and humanities), which, in turn, is opposed to a non­linear (pluralistic) approach that proclaims a theoretical variety and pluralism of methodological attitudes. This trend is determined by the desire to strengthen the epistemic foundations of social sciences and humanities through the recep­tion of concepts and approaches of other, “more successful” natural sciences or mathematical approaches from related fields in social sciences. Depending on how exactly the reception takes place and with which disciplines ties are built up, we distinguish three strategies for the development of naturalization. The first is a substitution strategy in which the social sciences and humanities not only borrow directly from natural sciences approaches, but also abandon their own specific research subject. The second strategy is an adaptation strategy. In this case, we are not talking about methodological substitution in its pure form, but about the possibility of partial reception of certain natural science theories and methods (or the reception of mathematical methods from related areas of social knowledge – for example, from the area of economic analysis) in accordance with the goals and objectives of social and humanitarian research (that is, the so­cial sciences and humanities retain their specific subject of research, and the me­thodological base expands through the use of scientific and mathematical meth­ods and data). And finally, the third is the validation strategy, in which the specific subject of social and humanitarian research is preserved. However, the borrow­ing of scientific methods occurs not at the stage of the research, but at the stage of assessing its results. In the paper we use specific examples from the social sci­ences and humanities to consider three strategies of reductionism (as naturaliza­tion) from the point of view of their consequences for the development of social sciences and humanities in an internalist perspective.
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Majumdar, Mukul, and Norman Schofield. "Mathematical Methods in Economics." Journal of Business & Economic Statistics 4, no. 2 (April 1986): 276. http://dx.doi.org/10.2307/1391329.

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Borowska, Maria. "Quantitative methods in the field of economic sciences." VUZF Review 5, no. 2 (June 29, 2020): 22–37. http://dx.doi.org/10.38188/2534-9228.20.2.03.

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The usage of quantitative tools for creating the mathematical models of functioning different economic facilities abounds the opportunity for better understanding and acquaintance of the surrounding reality. A lot of thinkers identify even universality of the particular branch of knowledge with the extent of its ‘mathematization’. Applying mathematical methods so called quantitative provide great and not to overestimate services not only in the science research of technique, physics, astronomy, biology and medicine, but also – within the qualitative methods- in the field of social science in the sphere of the control of the quality of production or in the process of service management or decision making. Complex nature of the social and economic phenomena requires making the usage of the most modern means and the ubiquitous computerization significantly confirms the usefulness of these methods. Progressing ‘mathematization’ and computerization of the science forces creating and applying quantitative (mathematical) models including economic science. The model of operating of studied system was considered in two variants. I. when the process of the product delivery to the store represents inclusively the subsystem of production and the subsystem of the transportation – it could be then said that the level of filling the store up is controlled by the aggregated process of the delivery of the product. when the process of the product delivery to the store takes into account explicate both the production process and also the operating of transportation subsystem, so it is then the structural process of the product delivery. Both in the aggregated and structural version, the analyses of the functioning of the system was made in three variants of the store filling: intermediate state of the store filling; zero state of the store filling that is lower barrier; the state of full storage of the store, that is the upper barrier. The result of my analyses are two proprietary probabilistic models of system operation which are presented through the system of differential equations both in the aggregated and structural variant. Probabilistic models of functioning of the system in both variants presented throughout the probabilistic model also enable determining sizing prognosis which are characteristic for the functioning of this system. These prognoses are transferred to the unit of the management system and they provide the premises to the streamline of its functioning. These tools create the basics of theoretical and methodological constructed computer programmes of the informative systems of decision-making support.
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Dissertations / Theses on the topic "Social Sciences Mathematical Methods"

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Hwang, Heungsun 1969. "Structural equation modeling by extended redundancy analysis." Thesis, McGill University, 2000. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=36954.

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A new approach to structural equation modeling based on so-called extended redundancy analysis (ERA) is proposed. In ERA, latent variables are obtained as exact linear combinations of observed variables, and model parameters are estimated by consistently minimizing a single criterion. As a result, the method can avoid limitations of covariance structure analysis (e.g., stringent distributional assumptions, improper solutions, and factor score indeterminacy) in addition to those of partial least squares (e.g., the lack of a global optimization procedure). The method is simple yet versatile enough to fit more complex models; e.g., those with higher-order latent variables and direct effects of observed variables. It can also fit a model to more than one sample simultaneously. Other relevant topics are also discussed, including data transformations, missing data, metric matrices, robust estimation, and efficient estimation. Examples are given to illustrate the proposed method.
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Cisneros-Molina, Myriam. "Mathematical methods for valuation and risk assessment of investment projects and real options." Thesis, University of Oxford, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.491350.

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In this thesis, we study the problems of risk measurement, valuation and hedging of financial positions in incomplete markets when an insufficient number of assets are available for investment (real options). We work closely with three measures of risk: Worst-Case Scenario (WCS) (the supremum of expected values over a set of given probability measures), Value-at-Risk (VaR) and Average Value-at-Risk (AVaR), and analyse the problem of hedging derivative securities depending on a non-traded asset, defined in terms of the risk measures via their acceptance sets. The hedging problem associated to VaR is the problem of minimising the expected shortfall. For WCS, the hedging problem turns out to be a robust version of minimising the expected shortfall; and as AVaR can be seen as a particular case of WCS, its hedging problem is also related to the minimisation of expected shortfall. Under some sufficient conditions, we solve explicitly the minimal expected shortfall problem in a discrete-time setting of two assets driven by correlated binomial models. In the continuous-time case, we analyse the problem of measuring risk by WCS, VaR and AVaR on positions modelled as Markov diffusion processes and develop some results on transformations of Markov processes to apply to the risk measurement of derivative securities. In all cases, we characterise the risk of a position as the solution of a partial differential equation of second order with boundary conditions. In relation to the valuation and hedging of derivative securities, and in the search for explicit solutions, we analyse a variant of the robust version of the expected shortfall hedging problem. Instead of taking the loss function $l(x) = [x]^+$ we work with the strictly increasing, strictly convex function $L_{\epsilon}(x) = \epsilon \log \left( \frac{1+exp\{−x/\epsilon\} }{ exp\{−x/\epsilon\} } \right)$. Clearly $lim_{\epsilon \rightarrow 0} L_{\epsilon}(x) = l(x)$. The reformulation to the problem for L_{\epsilon}(x) also allow us to use directly the dual theory under robust preferences recently developed in [82]. Due to the fact that the function $L_{\epsilon}(x)$ is not separable in its variables, we are not able to solve explicitly, but instead, we use a power series approximation in the dual variables. It turns out that the approximated solution corresponds to the robust version of a utility maximisation problem with exponential preferences $(U(x) = −\frac{1}{\gamma}e^{-\gamma x})$ for a preferenes parameter $\gamma = 1/\epsilon$. For the approximated problem, we analyse the cases with and without random endowment, and obtain an expression for the utility indifference bid price of a derivative security which depends only on the non-traded asset.
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Fang, Zhou. "Reweighting methods in high dimensional regression." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:26f8541a-9e2d-466a-84aa-e6850c4baba9.

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In this thesis, we focus on the application of covariate reweighting with Lasso-style methods for regression in high dimensions, particularly where p ≥ n. We apply a particular focus to the case of sparse regression under a-priori grouping structures. In such problems, even in the linear case, accurate estimation is difficult. Various authors have suggested ideas such as the Group Lasso and the Sparse Group Lasso, based on convex penalties, or alternatively methods like the Group Bridge, which rely on convergence under repetition to some local minimum of a concave penalised likelihood. We propose in this thesis a methodology that uses concave penalties to inspire a procedure whereupon we compute weights from an initial estimate, and then do a single second reweighted Lasso. This procedure -- the Co-adaptive Lasso -- obtains excellent results in empirical experiments, and we present some theoretical prediction and estimation error bounds. Further, several extensions and variants of the procedure are discussed and studied. In particular, we propose a Lasso style method of doing additive isotonic regression in high dimensions, the Liso algorithm, and enhance it using the Co-adaptive methodology. We also propose a method of producing rules based regression estimates for high dimensional non-parametric regression, that often outperforms the current leading method, the RuleFit algorithm. We also discuss extensions involving robust statistics applied to weight computation, repeating the algorithm, and online computation.
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Dunu, Emeka Samuel. "Comparing the Powers of Several Proposed Tests for Testing the Equality of the Means of Two Populations When Some Data Are Missing." Thesis, University of North Texas, 1994. https://digital.library.unt.edu/ark:/67531/metadc278198/.

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In comparing the means .of two normally distributed populations with unknown variance, two tests very often used are: the two independent sample and the paired sample t tests. There is a possible gain in the power of the significance test by using the paired sample design instead of the two independent samples design.
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Stewart, Joanna L. "Glasgow's spatial arrangement of deprivation over time : methods to measure it and meanings for health." Thesis, University of Glasgow, 2016. http://theses.gla.ac.uk/7936/.

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Background: Socio-economic deprivation is a key driver of population health. High levels of socio-economic deprivation have long been offered as the explanation for exceptionally high levels of mortality in Glasgow, Scotland. A number of recent studies have, however, suggested that this explanation is partial. Comparisons with Liverpool and Manchester suggest that mortality rates have been higher in Glasgow since the 1970s despite very similar levels of deprivation in these three cities. It has, therefore, been argued that there is an “excess” of mortality in Glasgow; that is, mortality rates are higher than would be expected given the city’s age, gender, and deprivation profile. A profusion of possible explanations for this excess has been proffered. One hypothesis is that the spatial arrangement of deprivation might be a contributing factor. Particular spatial configurations of deprivation have been associated with negative health impacts. It has been suggested that Glasgow experienced a distinct, and more harmful, development of spatial patterning of deprivation. Measuring the development of spatial arrangements of deprivation over time is technically challenging however. Therefore, this study brought together a number of techniques to compare the development of the spatial arrangement of deprivation in Glasgow, Liverpool and Manchester between 1971 and 2011. It then considered the plausibility of the spatial arrangement of deprivation as a contributing factor to Glasgow’s high levels of mortality. Methods: A literature review was undertaken to inform understandings of relationships between the spatial arrangement of deprivation and health outcomes. A substantial element of this study involved developing a methodology to facilitate temporal and inter-city comparisons of the spatial arrangement of deprivation. Key contributions of this study were the application of techniques to render and quantify whole-landscape perspectives on the development of spatial patterns of household deprivation, over time. This was achieved by using surface mapping techniques to map information relating to deprivation from the UK census, and then analysing these maps with spatial metrics. Results: There is agreement in the literature that the spatial arrangement of deprivation can influence health outcomes, but mechanisms and expected impacts are not clear. The temporal development of Glasgow’s spatial arrangement of deprivation exhibited both similarities and differences with Liverpool and Manchester. Glasgow often had a larger proportion of its landscape occupied with areas of deprivation, particularly in 1971 and 1981. Patch density and mean patch size (spatial metrics which provide an indication of fragmentation), however, were not found to have developed differently in Glasgow. Conclusion: The spatial extent of deprivation developed differently in Glasgow relative to Liverpool and Manchester as the results indicated that deprivation was substantially more spatially prevalent in Glasgow, this was particularly pronounced in 1971 and 1981. This implies that exposure of more affluent and deprived people to each other has been greater in Glasgow. Given that proximal inequality has been related to poor health outcomes, it would appear plausible that this may have adversely affected Glasgow’s mortality rates. If this is the case, however, it is unlikely that this will account for a substantial proportion of Glasgow’s excess mortality. Further research into Glasgow’s excess mortality is, therefore, required.
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Ciampa, Julia Grant. "Multilocus approaches to the detection of disease susceptibility regions : methods and applications." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:8f82a624-7d80-438c-af3e-68ce983ff45f.

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This thesis focuses on multilocus methods designed to detect single nucleotide polymorphisms (SNPs) that are associated with disease using case-control data. I study multilocus methods that allow for interaction in the regression model because epistasis is thought to be pervasive in the etiology of common human diseases. In contrast, the single-SNP models widely used in genome wide association studies (GWAS) are thought to oversimplify the underlying biology. I consider both pairwise interactions between individual SNPs and modular interactions between sets of biologically similar SNPs. Modular epistasis may be more representative of disease processes and its incorporation into regression analyses yields more parsimonious models. My methodological work focuses on strategies to increase power to detect susceptibility SNPs in the presence of genetic interaction. I emphasize the effect of gene-gene independence constraints and explore methods to relax them. I review several existing methods for interaction analyses and present their first empirical evaluation in a GWAS setting. I introduce the innovative retrospective Tukey score test (RTS) that investigates modular epistasis. Simulation studies suggest it offers a more powerful alternative to existing methods. I present diverse applications of these methods, using data from a multi-stage GWAS on prostate cancer (PRCA). My applied work is designed to generate hypotheses about the functionality of established susceptibility regions for PRCA by identifying SNPs that affect disease risk through interactions with them. Comparison of results across methods illustrates the impact of incorporating different forms of epistasis on inference about disease association. The top findings from these analyses are well supported by molecular studies. The results unite several susceptibility regions through overlapping biological pathways known to be disrupted in PRCA, motivating replication study.
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Churchhouse, Claire. "Bayesian methods for estimating human ancestry using whole genome SNP data." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:0cae8a4a-6989-485b-a7cb-0a03fb86096d.

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The past five years has seen the discovery of a wealth of genetics variants associated with an incredible range of diseases and traits that have been identified in genome- wide association studies (GWAS). These GWAS have typically been performed in in- dividuals of European descent, prompting a call for such studies to be conducted over a more diverse range of populations. These include groups such as African Ameri- cans and Latinos as they are recognised as bearing a disproportionately large burden of disease in the U.S. population. The variation in ancestry among such groups must be correctly accounted for in association studies to avoid spurious hits arising due to differences in ancestry between cases and controls. Such ancestral variation is not all problematic as it may also be exploited to uncover loci associated with disease in an approach known as admixture mapping, or to estimate recombination rates in admixed individuals. Many models have been proposed to infer genetic ancestry and they differ in their accuracy, the type of data they employ, their computational efficiency, and whether or not they can handle multi-way admixture. Despite the number of existing models, there is an unfulfilled requirement for a model that performs well even when the ancestral populations are closely related, is extendible to multi-way admixture scenarios, and can handle whole- genome data while remaining computationally efficient. In this thesis we present a novel method of ancestry estimation named MULTIMIX that satisfies these criteria. The underlying model we propose uses a multivariate nor- mal to approximate the distribution of a haplotype at a window of contiguous SNPs given the ancestral origin of that part of the genome. The observed allele types and the ancestry states that we aim to infer are incorporated in to a hidden Markov model to capture the correlations in ancestry that we expect to exist between neighbouring sites. We show via simulation studies that its performance on two-way and three-way admixture is competitive with state-of-the-art methods, and apply it to several real admixed samples of the International HapMap Project and the 1000 Genomes Project.
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Iotchkova, Valentina Valentinova. "Bayesian methods for multivariate phenotype analysis in genome-wide association studies." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:66fd61e1-a6e3-4e91-959b-31a3ec88967c.

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Most genome-wide association studies search for genetic variants associated to a single trait of interest, despite the main interest usually being the understanding of a complex genotype-phenotype network. Furthermore, many studies collect data on multiple phenotypes, each measuring a different aspect of the biological system under consideration, therefore it can often make sense to jointly analyze the phenotypes. However this is rarely the case and there is a lack of well developed methods for multiple phenotype analysis. Here we propose novel approaches for genome-wide association analysis, which scan the genome one SNP at a time for association with multivariate traits. The first half of this thesis focuses on an analytic model averaging approach which bi-partitions traits into associated and unassociated, fits all such models and measures evidence of association using a Bayes factor. The discrete nature of the model allows very fine control of prior beliefs about which sets of traits are more likely to be jointly associated. Using simulated data we show that this method can have much greater power than simpler approaches that do not explicitly model residual correlation between traits. On real data of six hematological parameters in 3 population cohorts (KORA, UKNBS and TwinsUK) from the HaemGen consortium, this model allows us to uncover an association at the RCL locus that was not identified in the original analysis but has been validated in a much larger study. In the second half of the thesis we propose and explore the properties of models that use priors encouraging sparse solutions, in the sense that genetic effects of phenotypes are shrunk towards zero when there is little evidence of association. To do this we explore and use spike and slab (SAS) priors. All methods combine both hypothesis testing, via calculation of a Bayes factor, and model selection, which occurs implicitly via the sparsity priors. We have successfully implemented a Variational Bayesian approach to fit this model, which provides a tractable approximation to the posterior distribution, and allows us to approximate the very high-dimensional integral required for the Bayes factor calculation. This approach has a number of desirable properties. It can handle missing phenotype data, which is a real feature of most studies. It allows for both correlation due to relatedness between subjects or population structure and residual phenotype correlation. It can be viewed as a sparse Bayesian multivariate generalization of the mixed model approaches that have become popular recently in the GWAS literature. In addition, the method is computationally fast and can be applied to millions of SNPs for a large number of phenotypes. Furthermore we apply our method to 15 glycans from 3 isolated population cohorts (ORCADES, KORCULA and VIS), where we uncover association at a known locus, not identified in the original study but discovered later in a larger one. We conclude by discussing future directions.
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Martins, Maria do Rosario Fraga Oliveira. "The use of nonparametric and semiparametric methods based on kernels in applied economics with an application to Portuguese female labour market." Doctoral thesis, Universite Libre de Bruxelles, 1998. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/211989.

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Eisman, Elyktra. "GIS-integrated mathematical modeling of social phenomena at macro- and micro- levels—a multivariate geographically-weighted regression model for identifying locations vulnerable to hosting terrorist safe-houses: France as case study." FIU Digital Commons, 2015. http://digitalcommons.fiu.edu/etd/2261.

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Adaptability and invisibility are hallmarks of modern terrorism, and keeping pace with its dynamic nature presents a serious challenge for societies throughout the world. Innovations in computer science have incorporated applied mathematics to develop a wide array of predictive models to support the variety of approaches to counterterrorism. Predictive models are usually designed to forecast the location of attacks. Although this may protect individual structures or locations, it does not reduce the threat—it merely changes the target. While predictive models dedicated to events or social relationships receive much attention where the mathematical and social science communities intersect, models dedicated to terrorist locations such as safe-houses (rather than their targets or training sites) are rare and possibly nonexistent. At the time of this research, there were no publically available models designed to predict locations where violent extremists are likely to reside. This research uses France as a case study to present a complex systems model that incorporates multiple quantitative, qualitative and geospatial variables that differ in terms of scale, weight, and type. Though many of these variables are recognized by specialists in security studies, there remains controversy with respect to their relative importance, degree of interaction, and interdependence. Additionally, some of the variables proposed in this research are not generally recognized as drivers, yet they warrant examination based on their potential role within a complex system. This research tested multiple regression models and determined that geographically-weighted regression analysis produced the most accurate result to accommodate non-stationary coefficient behavior, demonstrating that geographic variables are critical to understanding and predicting the phenomenon of terrorism. This dissertation presents a flexible prototypical model that can be refined and applied to other regions to inform stakeholders such as policy-makers and law enforcement in their efforts to improve national security and enhance quality-of-life.
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Books on the topic "Social Sciences Mathematical Methods"

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A mathematical primer for social statistics. Thousand Oaks, Calif: Sage Publications, 2009.

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Linguistic fuzzy logic methods in social sciences. Berlin, Germany: Springer, 2010.

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András, Simonovits. Mathematical methods in dynamic economics. New York: St. Martin's Press, 2000.

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András, Simonovits. Mathematical methods in dynamic economics. Basingstoke: Macmillan, 2000.

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Jason, Osborne, ed. Best practices in quantitative methods. Thousand Oaks, Calif: Sage Publications, 2008.

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L, Carlson William. Applied statistical methods: For business, economics, and the social sciences. Upper Saddle River, N.J: Prentice Hall, 1997.

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Brad, Stewart, ed. Social statistics: A user-friendly approach. Boston Mass: Allyn & Bacon, 1995.

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1942-, Sullivan Michael, Mizrahi Abe, and Schneider David I, eds. Mathematics for business, life sciences, and social sciences. 5th ed. New York: J. Wiley, 1993.

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1942-, Sullivan Michael, ed. Mathematics for business, life sciences, and social sciences. 5th ed. New York: Wiley, 1993.

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Popper, Shaffer Juliet, ed. The Role of models in nonexperimental social science: Two debates. Washington, D.C: American Educational Research Association and American Statistical Association, 1992.

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Book chapters on the topic "Social Sciences Mathematical Methods"

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De La Peña, Joseba Iñaki, and Noemí Peña-Miguel. "A Basic Social Pension for Everyone?" In Mathematical and Statistical Methods for Actuarial Sciences and Finance, 305–9. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89824-7_55.

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Kişi, Omer. "Convergence Methods for Double Sequences and Applications in Neutrosophic Normed Spaces." In Soft Computing Techniques in Engineering, Health, Mathematical and Social Sciences, 137–54. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003161707-9.

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Zou, Dahai, and Wei Chen. "The Characteristics of Mathematical Methods in the Wu Cao Suanjing and Its Social Background." In Why the Sciences of the Ancient World Matter, 603–45. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98361-1_11.

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Salvatori, Roberto. "Advanced Technologies for Social Communication: Methods and Techniques in Online Learning." In Mathematical-Statistical Models and Qualitative Theories for Economic and Social Sciences, 333–42. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54819-7_22.

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Corsi, Vincenzo. "Sociological Methods and Construction of Local Welfare in Italy." In Mathematical-Statistical Models and Qualitative Theories for Economic and Social Sciences, 413–23. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54819-7_28.

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Battelli, Flaviano, and Michal Fečkan. "On the Poincaré-Andronov-Melnikov Method for Modelling of Grazing Periodic Solutions in Discontinuous Systems." In Mathematical Modelling in Health, Social and Applied Sciences, 241–59. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2286-4_7.

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Díaz, Antonio, and Gloria Garrido. "Socially Responsible Investment, Should You Bother?" In Mathematical and Statistical Methods for Actuarial Sciences and Finance, 335–39. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89824-7_60.

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Basso, Antonella, and Stefania Funari. "Socially Responsible Mutual Funds: An Efficiency Comparison Among the European Countries." In Mathematical and Statistical Methods for Actuarial Sciences and Finance, 69–79. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-02499-8_6.

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Gal, Iddo, James Nicholson, and Jim Ridgway. "A Conceptual Framework for Civic Statistics and Its Educational Applications." In Statistics for Empowerment and Social Engagement, 37–66. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-20748-8_3.

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AbstractThis chapter presents a comprehensive conceptual framework of 11 facets and tools which together describe the knowledge, skills and dispositions that (young) adults need in order to comprehend, critically evaluate, communicate about, and engage with Civic Statistics regarding ‘burning’ societal issues, and that may enhance citizen empowerment. The framework is organized around three key dimensions involving engagement & action, knowledge, and enabling processes. It identifies knowledge-bases covering meaning for society and policy and critical evaluation and reflection; selected statistical and mathematical constructs and skills; core literacy and mathematical skills; understanding models and modelling, multivariate ideas and textual and rich visual representations; knowledge of research and data production methods and extensions related to official statistics and risk on the societal level; and it emphasises the importance of appropriate dispositions, critical stance, and habits of mind. We offer examples and curriculum tasks that illustrate each of the 11 facets and their interconnectedness. We also describe the use of a ‘radar plot’ tool to support the analysis of how balanced are prospective class activities or test items in terms of covering the 11 facets and tools. The chapter ends with a brief discussion of the implications of the conceptual model and its 11 facets for planning curricula, instruction, and assessments that can promote teaching and learning about Civic Statistics within mathematics education, statistics and data science education, and related disciplines.
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Gal, Iddo, Jim Ridgway, James Nicholson, and Joachim Engel. "Implementing Civic Statistics: An Agenda for Action." In Statistics for Empowerment and Social Engagement, 67–96. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-20748-8_4.

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AbstractThe first three chapters of this book have identified societal demands for understanding Civic Statistics (Chap. 1), described specific features of the statistical and mathematical information citizens receive about civic issues (Chap. 2), and mapped out the facets and tools (skills, knowledge, mental and motivational tools) needed to critically understand such statistical and mathematical information about society (Chap. 3). The present chapter examines issues that are essential for promoting necessary changes in the teaching and learning of Civic Statistics, which are needed for empowering citizens to engage with and analyze data sources and data-informed reasoning about burning issues in society, and critically interpret messages related to Civic Statistics encountered in the news media, social networks and related digital sources. The chapter first provides further illustrations of activities or tasks pertaining to Civic Statistics and shows how to analyse task demands in terms of the facets and tools they require. Then, general questions are examined regarding the all-important alignment of the features of Civic Statistics and their demands with curriculum plans and learning goals, classroom teaching practices, and assessment methods. We provide some guidelines for developing assessment items relevant to Civic Statistics. Finally, the chapter presents six broad recommendations related to changes in systemic issues that can promote attention to and critical understanding of Civic Statistics, at the school and university levels, and which can improve effective instruction and assessment in this regard, within mathematics education, statistics and data science education, and related disciplines.
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Conference papers on the topic "Social Sciences Mathematical Methods"

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Trynkin, V. V. "Mathematical methods of economic and human world." In IX International symposium «Humanities and Social Sciences in Europe: Achievements and Perspectives». Viena: East West Association GmbH, 2016. http://dx.doi.org/10.20534/ix-symposium-9-284-288.

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Ondruskova, Eva. "THE USE OF THE MATHEMATICAL METHODS IN PREDICTING SALES OF CONSTRUCTION COMPANIES." In 4th International Multidisciplinary Scientific Conference on Social Sciences and Arts SGEM2017. Stef92 Technology, 2017. http://dx.doi.org/10.5593/sgemsocial2017/13/s03.091.

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Yuryevna, Kropacheva Nataliya, and Fedorova Maria Yuryevna. "Introduction of Mathematical Methods in Teaching Humanities Students." In Proceedings of the 2nd International Conference on Education Science and Social Development (ESSD 2019). Paris, France: Atlantis Press, 2019. http://dx.doi.org/10.2991/essd-19.2019.19.

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Li, Jianjun, and Junjie Zhu. "The Analysis of Teaching Methods� Reformation Based on Mathematical Modeling." In 2nd International Conference on Science and Social Research (ICSSR 2013). Paris, France: Atlantis Press, 2013. http://dx.doi.org/10.2991/icssr-13.2013.19.

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Alessio, Danielle, D. Marc Kilgour, Ilias Kotsireas, Roderick Melnik, and Brian West. "Game Theory and Social Psychology: Conformity Games." In ADVANCES IN MATHEMATICAL AND COMPUTATIONAL METHODS: ADDRESSING MODERN CHALLENGES OF SCIENCE, TECHNOLOGY, AND SOCIETY. AIP, 2011. http://dx.doi.org/10.1063/1.3663496.

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Lee, Ken Voon. ""G.P.S Matrices" programme: A method to improve the mastery level of social science students in matrices operations." In PROCEEDINGS OF THE 20TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES: Research in Mathematical Sciences: A Catalyst for Creativity and Innovation. AIP, 2013. http://dx.doi.org/10.1063/1.4801245.

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Yang, Bodan, Chenxi Xia, Shangbin Ye, and Jiajin Chen. "Analysis of the Premium of American Option Based on both Mathematical Method and Python." In 2022 International Conference on Social Sciences and Humanities and Arts (SSHA 2022). Paris, France: Atlantis Press, 2022. http://dx.doi.org/10.2991/assehr.k.220401.064.

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Hasanah, Nurlayli, Diah Harmawati, and Minuk Riyana. "The Effect of Cooperative Learning Methods and Interest in Learning to the Ability Sort the Mathematical Pattern." In Proceedings of the International Conference on Social Science 2019 (ICSS 2019). Paris, France: Atlantis Press, 2019. http://dx.doi.org/10.2991/icss-19.2019.214.

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Albeanu, Grigore, Alexandra stefania Moloiu, and Florin Popentiu vladicescu. "RECENT COMPUTATIONAL INTELLIGENCE DEVELOPMENTS: TECHNICAL AND SOCIAL ASPECTS." In eLSE 2020. University Publishing House, 2020. http://dx.doi.org/10.12753/2066-026x-20-056.

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Computational Intelligence (CI) is a dynamic field of research, covering a large range of processing methods and providing value to many real life applications. From fuzzy reasoning, through evolutionary computation to machine learning (ML), important CI paradigms proved value in science and technology. However, learning from data through examples, as a ML way of thinking, is the main characteristic of the new smart systems. Old systems used pre-programmed rules to help a decisional process mainly human centered. Machine learning is developed taking into acount methods from computer science, statistics, and data science. Learning from data is possible by processes of supervised learning, unsupervised learning, semi-supervised learning, reinformcement learning, transduction, and learning to learn (inductive). Mainly, mathematical support is based on optimisation techniques for neural network training. Matlab, Python and various frameworks belong to technological support for implementation, and testing. This paper gives a broad view on recent computational intelligence algorithms and presents some appropriate case studies covering character recognition, electrocardiogram (ECG) analysis for individual identification, and robust face recognition. Deep learning approach is used for robust face recognition. Experiments with some multilayer neural network architectures are presented.The performance of such identification systems depends not only on the method used for feature extraction but also on the type of matching algorithm, and the interval of time allocated for training. Computational Intelligence (CI) is a dynamic field of research, covering a large range of processing methods and providing value to many real life applications. From fuzzy reasoning, through evolutionary computation to machine learning (ML), important CI paradigms proved value in science and technology. However, learning from data through examples, as a ML way of thinking, is the main characteristic of the new smart systems. Old systems used pre-programmed rules to help a decisional process mainly human centered.
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Dvoryatkina, Svetlana. "IMPROVEMENT OF METHODS OF AUTOMATED ESTIMATION OF THE FORMATION OF BASIC COMPETENCIES ON MATHEMATICS BASED ON FUZZY LOGIC." In 5th SGEM International Multidisciplinary Scientific Conferences on SOCIAL SCIENCES and ARTS SGEM2018. STEF92 Technology, 2018. http://dx.doi.org/10.5593/sgemsocial2018/3.5/s13.053.

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Reports on the topic "Social Sciences Mathematical Methods"

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Pottinger, Laura, Amy Barron, Alison Browne, and Sarah Marie Hall. Should we be spending more time talking about methods? Royal Geographical Society (with IBG), April 2022. http://dx.doi.org/10.55203/kzeb3802.

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Yaremchuk, Olesya. TRAVEL ANTHROPOLOGY IN JOURNALISM: HISTORY AND PRACTICAL METHODS. Ivan Franko National University of Lviv, February 2021. http://dx.doi.org/10.30970/vjo.2021.49.11069.

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Our study’s main object is travel anthropology, the branch of science that studies the history and nature of man, socio-cultural space, social relations, and structures by gathering information during short and long journeys. The publication aims to research the theoretical foundations and genesis of travel anthropology, outline its fundamental principles, and highlight interaction with related sciences. The article’s defining objectives are the analysis of the synthesis of fundamental research approaches in travel anthropology and their implementation in journalism. When we analyze what methods are used by modern authors, also called «cultural observers», we can return to the localization strategy, namely the centering of the culture around a particular place, village, or another spatial object. It is about the participants-observers and how the workplace is limited in space and time and the broader concept of fieldwork. Some disciplinary practices are confused with today’s complex, interactive cultural conjunctures, leading us to think of a laboratory of controlled observations. Indeed, disciplinary approaches have changed since Malinowski’s time. Based on the experience of fieldwork of Svitlana Aleksievich, Katarzyna Kwiatkowska-Moskalewicz, or Malgorzata Reimer, we can conclude that in modern journalism, where the tools of travel anthropology are used, the practical methods of complexity, reflexivity, principles of openness, and semiotics are decisive. Their authors implement both for stable localization and for a prevailing transition.
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Ivanova, Halyna I., Olena O. Lavrentieva, Larysa F. Eivas, Iuliia O. Zenkovych, and Aleksandr D. Uchitel. The students' brainwork intensification via the computer visualization of study materials. [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3859.

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The paper the approaches to the intensification of the students’ brainwork by means of computer visualization of study material have been disclosed. In general, the content of students’ brainwork has been presented as a type of activity providing the cognitive process, mastering the techniques and ways of thinking, developing the capabilities and abilities of the individual, the product of which is a certain form of information, as a result of the brainwork the outlook of the subject of work is enriched. It is shown the visualization is the process of presenting data in the form of an image with the aim of maximum ease of understanding; the giving process of visual form to any mental object. In the paper the content, techniques, methods and software for creating visualization tools for study material has exposed. The essence and computer tools for creating such types of visualization of educational material like mind maps, supporting notes and infographics have been illustrated; they have been concretized from the point of view of application in the course of studying the mathematical sciences. It is proved the use of visualization tools for study materials helps to increase the intensity and effectiveness of students’ brainwork. Based on the results of an empirical study, it has been concluded the visualization of study materials contributes to the formation of students’ key intellectual competencies and forming their brainwork culture.
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Bodnenko, Dmytro M., Halyna A. Kuchakovska, Volodymyr V. Proshkin, and Oksana S. Lytvyn. Using a virtual digital board to organize student’s cooperative learning. [б. в.], November 2020. http://dx.doi.org/10.31812/123456789/4419.

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The article substantiates the importance of using a virtual digital board to organize student’s cooperative learning in the conditions of distance education, incl. social distance (for the quarantine period 2020). The main advantages of using a virtual digital board are outlined and their functions for the organization of cooperative education are compared. An analysis of the benefits of using virtual digital boards and a survey of experts made it possible to identify the most popular virtual digital boards: Wiki-Wall, Glogster, PadLet, Linoit, Twidla, Trello, Realtimeboard (Miro), Rizzoma. The comparison of the functions of virtual digital boards outlines their ability to organize students’ cooperative learning. The structure of the module E-Learning “Creating education content with tools of virtual digital board Padlet” is presented in the system LMS Moodle. The results of the experiment are presented, which show the effectiveness of the use of instruments of the virtual digital board to organize student’s cooperative learning. Perspectives of researches in developing methods of using a virtual digital board by students of natural-mathematical specialties are determined.
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Perdigão, Rui A. P. New Horizons of Predictability in Complex Dynamical Systems: From Fundamental Physics to Climate and Society. Meteoceanics, October 2021. http://dx.doi.org/10.46337/211021.

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Discerning the dynamics of complex systems in a mathematically rigorous and physically consistent manner is as fascinating as intimidating of a challenge, stirring deeply and intrinsically with the most fundamental Physics, while at the same time percolating through the deepest meanders of quotidian life. The socio-natural coevolution in climate dynamics is an example of that, exhibiting a striking articulation between governing principles and free will, in a stochastic-dynamic resonance that goes way beyond a reductionist dichotomy between cosmos and chaos. Subjacent to the conceptual and operational interdisciplinarity of that challenge, lies the simple formal elegance of a lingua franca for communication with Nature. This emerges from the innermost mathematical core of the Physics of Coevolutionary Complex Systems, articulating the wealth of insights and flavours from frontier natural, social and technical sciences in a coherent, integrated manner. Communicating thus with Nature, we equip ourselves with formal tools to better appreciate and discern complexity, by deciphering a synergistic codex underlying its emergence and dynamics. Thereby opening new pathways to see the “invisible” and predict the “unpredictable” – including relative to emergent non-recurrent phenomena such as irreversible transformations and extreme geophysical events in a changing climate. Frontier advances will be shared pertaining a dynamic that translates not only the formal, aesthetical and functional beauty of the Physics of Coevolutionary Complex Systems, but also enables and capacitates the analysis, modelling and decision support in crucial matters for the environment and society. By taking our emerging Physics in an optic of operational empowerment, some of our pioneering advances will be addressed such as the intelligence system Earth System Dynamic Intelligence and the Meteoceanics QITES Constellation, at the interface between frontier non-linear dynamics and emerging quantum technologies, to take the pulse of our planet, including in the detection and early warning of extreme geophysical events from Space.
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Greenberg, Jane, Samantha Grabus, Florence Hudson, Tim Kraska, Samuel Madden, René Bastón, and Katie Naum. The Northeast Big Data Innovation Hub: "Enabling Seamless Data Sharing in Industry and Academia" Workshop Report. Drexel University, March 2017. http://dx.doi.org/10.17918/d8159v.

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Increasingly, both industry and academia, in fields ranging from biology and social sciences to computing and engineering, are driven by data (Provost & Fawcett, 2013; Wixom, et al, 2014); and both commercial success and academic impact are dependent on having access to data. Many organizations collecting data lack the expertise required to process it (Hazen, et al, 2014), and, thus, pursue data sharing with researchers who can extract more value from data they own. For example, a biosciences company may benefit from a specific analysis technique a researcher has developed. At the same time, researchers are always on the search for real-world data sets to demonstrate the effectiveness of their methods. Unfortunately, many data sharing attempts fail, for reasons ranging from legal restrictions on how data can be used—to privacy policies, different cultural norms, and technological barriers. In fact, many data sharing partnerships that are vital to addressing pressing societal challenges in cities, health, energy, and the environment are not being pursued due to such obstacles. Addressing these data sharing challenges requires open, supportive dialogue across many sectors, including technology, policy, industry, and academia. Further, there is a crucial need for well-defined agreements that can be shared among key stakeholders, including researchers, technologists, legal representatives, and technology transfer officers. The Northeast Big Data Innovation Hub (NEBDIH) took an important step in this area with the recent "Enabling Seamless Data Sharing in Industry and Academia" workshop, held at Drexel University September 29-30, 2016. The workshop brought together representatives from these critical stakeholder communities to launch a national dialogue on challenges and opportunities in this complex space.
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Tucker-Blackmon, Angelicque. Engagement in Engineering Pathways “E-PATH” An Initiative to Retain Non-Traditional Students in Engineering Year Three Summative External Evaluation Report. Innovative Learning Center, LLC, July 2020. http://dx.doi.org/10.52012/tyob9090.

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The summative external evaluation report described the program's impact on faculty and students participating in recitation sessions and active teaching professional development sessions over two years. Student persistence and retention in engineering courses continue to be a challenge in undergraduate education, especially for students underrepresented in engineering disciplines. The program's goal was to use peer-facilitated instruction in core engineering courses known to have high attrition rates to retain underrepresented students, especially women, in engineering to diversify and broaden engineering participation. Knowledge generated around using peer-facilitated instruction at two-year colleges can improve underrepresented students' success and participation in engineering across a broad range of institutions. Students in the program participated in peer-facilitated recitation sessions linked to fundamental engineering courses, such as engineering analysis, statics, and dynamics. These courses have the highest failure rate among women and underrepresented minority students. As a mixed-methods evaluation study, student engagement was measured as students' comfort with asking questions, collaboration with peers, and applying mathematics concepts. SPSS was used to analyze pre-and post-surveys for statistical significance. Qualitative data were collected through classroom observations and focus group sessions with recitation leaders. Semi-structured interviews were conducted with faculty members and students to understand their experiences in the program. Findings revealed that women students had marginalization and intimidation perceptions primarily from courses with significantly more men than women. However, they shared numerous strategies that could support them towards success through the engineering pathway. Women and underrepresented students perceived that they did not have a network of peers and faculty as role models to identify within engineering disciplines. The recitation sessions had a positive social impact on Hispanic women. As opportunities to collaborate increased, Hispanic womens' social engagement was expected to increase. This social engagement level has already been predicted to increase women students' persistence and retention in engineering and result in them not leaving the engineering pathway. An analysis of quantitative survey data from students in the three engineering courses revealed a significant effect of race and ethnicity for comfort in asking questions in class, collaborating with peers outside the classroom, and applying mathematical concepts. Further examination of this effect for comfort with asking questions in class revealed that comfort asking questions was driven by one or two extreme post-test scores of Asian students. A follow-up ANOVA for this item revealed that Asian women reported feeling excluded in the classroom. However, it was difficult to determine whether these differences are stable given the small sample size for students identifying as Asian. Furthermore, gender differences were significant for comfort in communicating with professors and peers. Overall, women reported less comfort communicating with their professors than men. Results from student metrics will inform faculty professional development efforts to increase faculty support and maximize student engagement, persistence, and retention in engineering courses at community colleges. Summative results from this project could inform the national STEM community about recitation support to further improve undergraduate engineering learning and educational research.
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Chornodon, Myroslava. FEAUTURES OF GENDER IN MODERN MASS MEDIA. Ivan Franko National University of Lviv, February 2021. http://dx.doi.org/10.30970/vjo.2021.49.11064.

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The article clarifies of gender identity stereotypes in modern media. The main gender stereotypes covered in modern mass media are analyzed and refuted. The model of gender relations in the media is reflected mainly in the stereotypical images of men and woman. The features of the use of gender concepts in modern periodicals for women and men were determined. The most frequently used derivatives of these macroconcepts were identified and analyzed in detail. It has been found that publications for women and men are full of various gender concepts that are used in different contexts. Ingeneral, theanalysisofthe concept-maximums and concept-minimum gender and their characteristics is carried out in the context of gender stereotypes that have been forme dand function in the society, system atizing the a ctual presentations. The study of the gender concept is relevant because it reveals new trends and features of modern gender images. Taking into account the special features of gender-labeled periodicals in general and the practical absence of comprehensive scientific studies of the gender concept in particular, there is a need to supplement Ukrainian science with this topic. Gender psychology, which is served by methods of various sciences, primarily sociological, pedagogical, linguistic, psychological, socio-psychological. Let us pay attention to linguistic and psycholinguistic methods in gender studies. Linguistic methods complement intelligence research tasks, associated with speech, word and text. Psycholinguistic methods used in gender psychology (semantic differential, semantic integral, semantic analysis of words and texts), aimed at studying speech messages, specific mechanisms of origin and perception, functions of speech activity in society, studying the relationship between speech messages and gender properties participants in the communication, to analyze the linguistic development in connection with the general development of the individual. Nowhere in gender practice there is the whole arsenal of psychological methods that allow you to explore psychological peculiarities of a person like observation, experiments, questionnaires, interviews, testing, modeling, etc. The methods of psychological self-diagnostics include: the gender aspect of the own socio-psychological portrait, a gender biography as a variant of the biographical method, aimed at the reconstruction of individual social experience. In the process of writing a gender autobiography, a person can understand the characteristics of his gender identity, as well as ways and means of their formation. Socio-psychological methods of studying gender include the study of socially constructed women’s and men’s roles, relationships and identities, sexual characteristics, psychological characteristics, etc. The use of gender indicators and gender approaches as a means of socio-psychological and sociological analysis broadens the subject boundaries of these disciplines and makes them the subject of study within these disciplines. And also, in the article a combination of concrete-historical, structural-typological, system-functional methods is implemented. Descriptive and comparative methods, method of typology, modeling are used. Also used is a method of content analysis for the study of gender content of modern gender-stamped journals. It was he who allowed quantitatively to identify and explore the features of the gender concept in the pages of periodicals for women and men. A combination of historical, structural-typological, system-functional methods is also implemented in the article. Descriptive and comparative methods, method of typology, modeling are used. A method of content analysis for the study of gender content of modern gender-labeled journals is also used. It allowed to identify and explore the features of the gender concept quantitatively in the periodicals for women and men. The conceptual perception and interpretation of the gender concept «woman», which is highlighted in the modern gender-labeled press in Ukraine, requires the elaboration of the polyfunctionality of gender interpretations, the comprehension of the metaphorical perception of this image and its role and purpose in society. A gendered approach to researching the gender content of contemporary periodicals for women and men. Conceptual analysis of contemporary gender-stamped publications within the gender conceptual sphere allows to identify and correlate the meta-gender and gender concepts that appear in society.
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Computational Biology: Development in the Field of Medicine. Science Repository, April 2021. http://dx.doi.org/10.31487/sr.blog.31.

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Computational biology involves the development and application of analytical-data and theoretical methods, computational simulation techniques, and mathematical modeling to the study of biological, behavioral, ecological, and social systems.
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