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Добірка наукової літератури з теми "Social Science"

Автор: Grafiati

Опубліковано: 4 червня 2021

Оновлено: 30 липня 2024

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Статті в журналах з теми "Social Science"

1

Lazer, D., A. Pentland, L. Adamic, S. Aral, A. L. Barabasi, D. Brewer, N. Christakis, et al. "SOCIAL SCIENCE: Computational Social Science." Science 323, no. 5915 (February 6, 2009): 721–23. http://dx.doi.org/10.1126/science.1167742.

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2

Fouché, Rayvon. "Embracing the Social in Social Science." Issues in Science and Technology 40, no. 3 (April 1, 2024): 78–83. http://dx.doi.org/10.58875/czwz2076.

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3

Kertzer, David I. "Social Anthropology and Social Science History." Social Science History 33, no. 1 (2009): 1–16. http://dx.doi.org/10.1017/s0145553200010889.

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Анотація:

In the 1970s, when the social science history movement emerged in the United States, leading to the founding of the Social Science History Association, a simultaneous movement arose in which historians looked to cultural anthropology for inspiration. Although both movements involved historians turning to social sciences for theory and method, they reflected very different views of the nature of the historical enterprise. Cultural anthropology, most notably as preached by Clifford Geertz, became a means by which historians could find a theoretical basis in the social sciences for rejecting a scientific paradigm. This article examines this development while also exploring the complex ways cultural anthropology has embraced—and shunned—history in recent years.

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4

Fay, Brian. "For Science in the Social Sciences." Philosophy of the Social Sciences 36, no. 2 (June 2006): 227–40. http://dx.doi.org/10.1177/0048393106287243.

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5

Dooge, James C. I. "Hydrologic science and social problems." Arbor 164, no. 646 (October 30, 1999): 191–202. http://dx.doi.org/10.3989/arbor.1999.i646.1585.

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6

Campos, Rita, José Monteiro, and Cláudia Carvalho. "Engaged Citizen Social Science or the public participation in social science research." Journal of Science Communication 20, no. 06 (October 11, 2021): A06. http://dx.doi.org/10.22323/2.20060206.

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Анотація:

Acknowledging the consolidation of citizen science, this paper aims to foster a collective debate on two visible gaps of the field. First, how to overcome the limited participation of social sciences and humanities in the broader field of citizen science, still dominated by natural sciences. Second, how to develop a citizen social science that allows for an active participation of citizens and for a critical engagement with contemporary societies. The authors coordinate a state-sponsored program of scientific dissemination within a Portuguese research institution and this paper intends to lay the groundwork for a future project of Citizen Social Science based on a new concept of “engaged citizen social science”.

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7

Benton, Ted, and Roget Trigg. "Understanding Social Science: A philosophical Introduction to the Social Sciences." Contemporary Sociology 16, no. 1 (January 1987): 95. http://dx.doi.org/10.2307/2071237.

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8

Wallach, Hanna. "Computational social science ≠ computer science + social data." Communications of the ACM 61, no. 3 (February 21, 2018): 42–44. http://dx.doi.org/10.1145/3132698.

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9

Chung, Emma, John Cromby, Dimitris Papadopoulos, and Cristina Tufarelli. "Social Epigenetics: A Science of Social Science?" Sociological Review 64, no. 1_suppl (March 2016): 168–85. http://dx.doi.org/10.1111/2059-7932.12019.

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10

Chung, Emma, John Cromby, Dimitris Papadopoulos, and Cristina Tufarelli. "Social epigenetics: a science of social science?" Sociological Review Monographs 64, no. 1 (March 2016): 168–85. http://dx.doi.org/10.1002/2059-7932.12019.

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Дисертації з теми "Social Science"

1

Blomley, Matthew. "The new science, social science, and society." Thesis, University of Cambridge, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.620289.

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2

Lambert, Ian J. "Realism and social science." Thesis, University of Sussex, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.278516.

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3

Booth, M. A. "Elaboration and social science." Thesis, Booth, M.A. (1988) Elaboration and social science. PhD thesis, Murdoch University, 1988. https://researchrepository.murdoch.edu.au/id/eprint/50563/.

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Анотація:

Social science is in jeopardy, both from attempts to make it like other sciences, and from the emphasis on human creativity and meanings, which would embed studies of society within the humanities. The multiplicity of theoretical positions within the social sciences, along with that multiplicity which is present in any person's social understanding, needs analysing in terms neither of 'meaning', nor of 'context', but through an understanding of the process of 'elaboration', by which multiplicity develops. Rather than awaiting a new theoretical 'paradigm', permitting the integration of systematic knowledge about human society, social scientists need more mutual recognition of their already shared approach to understanding. Elaboration in intellectual work is, like the secondary process of Freud, a process utilizing both the heterogeneity of past understanding, and an awareness which goes beyond any previous interpretation; the interplay of these in elaboration brings together and articulates a new aspect of multiplicity. Accounts of consciousness, and of epistemology and ontology, which do not lead to any sense of elaboration except that of the increasing of complexity by the adding of further details, are contrasted with the duality - in terms of the discrete and the holistic - which recent attempts at modelling brain functioning have suggested. By linking these to Freud's argument about the theoretical complexity required by any conceptualization of consciousness, the understanding of elaboration is developed and then traced in examples of recent usage. Processes of fragmentation and integration occur in social change, as well as in the development of social understanding. In neither case is their 'truth' an appropriate criterion for responding to these elaborations. Evaluating their 'scope', and so taking account of the comprehensiveness of the elaborations, is more useful in the human condition of multiplicity. Judgments of scope are a basis for comparing positions that are incommensurable, i.e. relativism as an epistemological problem is replaced by the practical methodological issues introduced by considering the discrete and holistic aspects of any elaboration. The ontological interplay of discrete and holistic processes in social practices and institutions has been elaborated recently in ways invoking Freud's terminology; construing this as elaboration provides a way of conceiving the duality of social structure. Elaborating social understanding in terms of this way of representing structural and intellectual change underlines the importance for social science of criteria for evaluating the process of elaboration.

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4

Hadder, R. Neill (Richard Neill). "Techniques of Social-science-fiction." Thesis, University of North Texas, 1995. https://digital.library.unt.edu/ark:/67531/metadc278249/.

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This thesis includes an original science-fiction novella entitled "The Hunted" and accompanying commentary which illustrates how anthropological fiction can use characterization, setting, and conflict to build effective inter-subjective models.

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5

Yu, Jingyuan. "Discovering Twitter through Computational Social Science Methods." Doctoral thesis, Universitat Autònoma de Barcelona, 2021. http://hdl.handle.net/10803/671609.

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Visibilitzant la vida quotidiana de la gent, Twitter s'ha convertit en una de les plataformes d'intercanvi d'informació més importants i ha atret ràpidament l'atenció dels científics. Investigadors de tot el món s'han centrat en les ciències socials i en els estudis d'Internet amb dades de Twitter com a mostra del món real, i en l'última dècada s'han dissenyat nombroses eines d'anàlisis i algorismes. La present tesi doctoral consta de tres recerques, en primer lloc, donats els 14 anys (fins a 2020) d'història des de la fundació de Twitter, hem assistit a una explosió de publicacions científiques relacionades, però el panorama actual de la recerca en aquesta plataforma de mitjans socials continuava sent desconegut. Per a omplir aquest buit de recerca, vam fer una anàlisi bibliomètrica dels estudis relacionats amb Twitter per a analitzar com van evolucionar els estudis de Twitter al llarg del temps, i per a proporcionar una descripció general de l'entorn acadèmic de recerca de Twitter des d'un nivell macro. En segon lloc, atès que hi ha moltes eines de programari analític que estan disponibles actualment per a la recerca en Twitter, una pregunta pràctica per als investigadors júnior és com triar el programari més apropiat per al seu propi projecte de recerca. Per a resoldre aquest problema, vam fer una revisió del programari per a alguns dels sistemes integrats que es consideren més rellevants per a la recerca en ciències socials. Atès que els investigadors júnior en ciències socials poden enfrontar-se a possibles limitacions financeres, vam reduir el nostre abast per a centrar-nos únicament en el programari gratuït i de baix cost. En tercer lloc, donada l'actual crisi de salut pública, hem observat que els mitjans de comunicació social són una de les fonts d'informació i notícies més accessibles per al públic. Durant una pandèmia, la forma en què s'emmarquen els problemes de salut i les malalties en la premsa influeix en la comprensió del públic sobre l'actual brot epidèmic i les seves actituds i comportaments. Per tant, decidim usar Twitter com una font de notícies de fàcil accés per a analitzar l'evolució dels marcs de notícies espanyols durant la pandèmia COVID-19. En general, les tres recerques s'han associat estretament amb l'aplicació de mètodes computacionals, incloent la recol·lecció de dades en línia, la mineria de textos, l'anàlisi de xarxes i la visualització de dades. Aquest projecte de doctorat ha mostrat com la gent estudia i utilitza Twitter des de tres nivells diferents: el nivell acadèmic, el nivell pràctic i el nivell empíric.
Visibilizando la vida cotidiana de la gente, Twitter se ha convertido en una de las plataformas de intercambio de información más importantes y ha atraído rápidamente la atención de los científicos. Investigadores de todo el mundo se han centrado en las ciencias sociales y en los estudios de Internet con datos de Twitter como muestra del mundo real, y en la última década se han diseñado numerosas herramientas de análisis y algoritmos. La presente tesis doctoral consta de tres investigaciones, en primer lugar, dados los 14 años (hasta 2020) de historia desde la fundación de Twitter, hemos asistido a una explosión de publicaciones científicas relacionadas, pero el panorama actual de la investigación en esta plataforma de medios sociales seguía siendo desconocido. Para llenar este vacío de investigación, hicimos un análisis bibliométrico de los estudios relacionados con Twitter para analizar cómo evolucionaron los estudios de Twitter a lo largo del tiempo, y para proporcionar una descripción general del entorno académico de investigación de Twitter desde un nivel macro. En segundo lugar, dado que hay muchas herramientas de software analítico que están disponibles actualmente para la investigación en Twitter, una pregunta práctica para los investigadores junior es cómo elegir el software más apropiado para su propio proyecto de investigación. Para resolver este problema, hicimos una revisión del software para algunos de los sistemas integrados que se consideran más relevantes para la investigación en ciencias sociales. Dado que los investigadores junior en ciencias sociales pueden enfrentarse a posibles limitaciones financieras, redujimos nuestro alcance para centrarnos únicamente en el software gratuito y de bajo coste. En tercer lugar, dada la actual crisis de salud pública, hemos observado que los medios de comunicación social son una de las fuentes de información y noticias más accesibles para el público. Durante una pandemia, la forma en que se enmarcan los problemas de salud y las enfermedades en la prensa influye en la comprensión del público sobre el actual brote epidémico y sus actitudes y comportamientos. Por lo tanto, decidimos usar Twitter como una fuente de noticias de fácil acceso para analizar la evolución de los marcos de noticias españoles durante la pandemia COVID-19. En general, las tres investigaciones se han asociado estrechamente con la aplicación de métodos computacionales, incluyendo la recolección de datos en línea, la minería de textos, el análisis de redes y la visualización de datos. Este proyecto de doctorado ha mostrado cómo la gente estudia y utiliza Twitter desde tres niveles diferentes: el nivel académico, el nivel práctico y el nivel empírico.
As Twitter has covered up people’s daily life, it has became one of the most important information exchange platforms, and quickly attracted scientists’ attention. Researchers around the world have highly focused on social science and internet studies with Twitter data as a real world sample, and numerous analytics tools and algorithms have been designed in the last decade. The present doctoral thesis consists of three researches, first, given the 14 years (until 2020) of history since the foundation of Twitter, an explosion of related scientific publications have been witnessed, but the current research landscape on this social media platform remained unknown, to fill this research gap, we did a bibliometric analysis on Twitter-related studies to analyze how the Twitter studies evolved over time, and to provide a general description of the Twitter research academic environment from a macro level. Second, since there are many analytic software tools that are currently available for Twitter research, a practical question for junior researchers is how to choose the most appropriate software for their own research project, to solve this problem, we did a software review for some of the integrated frameworks that are considered most relevant for social science research, given that junior social science researchers may face possible financial constraints, we narrowed our scope to solely focus on the free and low-cost software. Third, given the current public health crisis, we have noticed that social media are one of the most accessed information and news sources for the public. During a pandemic, how health issues and diseases are framed in the news release impacts public’s understanding of the current epidemic outbreak and their attitudes and behaviors. Hence, we decided to use Twitter as an easy-access news source to analyze the evolution of the Spanish news frames during the COVID-19 pandemic. Overall, the three researches have closely associated with the application of computational methods, including online data collection, text mining, complex network and data visualization. And this doctoral project has discovered how people study and use Twitter from three different levels: the academic level, the practical level and the empirical level.

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6

Curry, Phyllis A. "Wife battering : a social (science) problem /." Access Digital Full Text version, 1989. http://pocketknowledge.tc.columbia.edu/home.php/bybib/10901462.

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7

Sivaramakrishnan, A. "Social science, professional authority and citizenship." Thesis, University of Southampton, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.382911.

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8

O'Connor, Brendan T. "Statistical Text Analysis for Social Science." Research Showcase @ CMU, 2014. http://repository.cmu.edu/dissertations/541.

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Анотація:

What can text corpora tell us about society? How can automatic text analysis algorithms efficiently and reliably analyze the social processes revealed in language production? This work develops statistical text analyses of dynamic social and news media datasets to extract indicators of underlying social phenomena, and to reveal how social factors guide linguistic production. This is illustrated through three case studies: first, examining whether sentiment expressed in social media can track opinion polls on economic and political topics (Chapter 3); second, analyzing how novel online slang terms can be very specific to geographic and demographic communities, and how these social factors affect their transmission over time (Chapters 4 and 5); and third, automatically extracting political events from news articles, to assist analyses of the interactions of international actors over time (Chapter 6). We demonstrate a variety of computational, linguistic, and statistical tools that are employed for these analyses, and also contribute MiTextExplorer, an interactive system for exploratory analysis of text data against document covariates, whose design was informed by the experience of researching these and other similar works (Chapter 2). These case studies illustrate recurring themes toward developing text analysis as a social science methodology: computational and statistical complexity, and domain knowledge and linguistic assumptions.

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9

Anzola, David. "The philosophy of computational social science." Thesis, University of Surrey, 2015. http://epubs.surrey.ac.uk/808102/.

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The thesis is a collection of six stand-alone chapters aimed at setting the foundations for the philosophy of computational social science. Agent-based modelling has been used for social research since the nineties. While at the beginning it was simply conceived as a methodological alternative, recently, the notion of ‘computational social science’ has started to be used to denote a separate disciplinary field. There are important differences with mainstream social science and traditional social research. Yet, the literature in the field has not accounted for these differences. Computational social science is a strongly practice-oriented field, where theoretical and philosophical concerns have been pushed into the background. This thesis presents an initial analysis of the methodology, epistemology and ontology of computational social science, by examining the following topics: 1) verification and validation and 2) modelling and theorising, 3) mechanisms 4) explanation 5) agency, action and interaction and 6) entities and process philosophy. Five general conclusions are drawn from the thesis. It is first argued that the wider ontological base in agent-based modelling allows for a new approach to traditional social dualisms, moving away from the methodological individualism that dominates computational social science. Second, the need to place a distinction between explanation and understanding and to make explanatory goals explicit is highlighted. Third, it is claimed that computational social science needs to pay attention to the social epistemology of the field, for this could provide important insights regarding values, ideologies and interests that underlie the practice of agent-based modelling. Fourth, it is suggested that a more robust theorisation regarding the experimental and model-based character of agent-based modelling should be developed. Finally, it is argued that the method can greatly contribute to the development of a processual account of social life.

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10

Ross, Derek Gilbert. "The Social Role of Popularized Science." Thesis, Virginia Tech, 2004. http://hdl.handle.net/10919/35372.

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In this thesis I will argue that popularized science books should adhere to normative criteria regarding the presentation, interpretation, and understanding of the natural sciences. The increasing popularity of popular science texts (PSTs) - based on sales, critical notice, and scholarly attention - indicates that they can function to interest and partially educate the lay public in scientific principals and practices. I will identify and analyze the narrative, rhetorical features of two popular science texts: Douglas Adams' Last Chance to See and Alan Lightman's Einstein's Dreams. These texts are selected based on a series of normative criteria, criteria constructed for the purpose of enhancing the public understanding of science. Additionally, these criteria are needed to help the lay public develop a proper appreciation of science. A proper appreciation of science, I argue, enables people to make better informed decisions regarding their own personal welfare and also that of the natural world. Finally, a proper appreciation of science, stimulated by PSTs, may help both scientists and the lay public reconceive the possibilities of narrative, public writing, and civic discourse.
Master of Arts

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Книги з теми "Social Science"

1

Valsiner, Jaan, ed. Social Philosophy of Science for the Social Sciences. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33099-6.

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2

American Bar Association. Standing Committee on Education About Communism and Its Contrast With Liberty Under Law., ed. Social science. Lexington, Mass: Lexington Books, 1994.

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3

Rudas, Tamás, and Gábor Péli, eds. Pathways Between Social Science and Computational Social Science. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-54936-7.

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4

Wright, James D. Social Problems, Social Issues, Social Science. New Brunswick : Transaction Publishers, [2016] | Collection of papers originally published in the journal Society.: Routledge, 2017. http://dx.doi.org/10.4324/9781315129716.

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5

Bulmer, Martin. Social Science and Social Policy. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003246299.

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6

Bulmer, Martin. Social science and social policy. London: Allen & Unwin, 1986.

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7

Lance, Shotland R., and Mark Melvin M, eds. Social science and social policy. Beverly Hills: Sage Publications, 1985.

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8

Gilbert, Nigel. Computational Social Science. 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications Ltd, 2010. http://dx.doi.org/10.4135/9781446261088.

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9

Scott, Jacqueline, and Yu Xie. Quantitative Social Science. 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications Ltd, 2005. http://dx.doi.org/10.4135/9781446263198.

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10

Alvarez, R. Michael, ed. Computational Social Science. Cambridge: Cambridge University Press, 2016. http://dx.doi.org/10.1017/cbo9781316257340.

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Частини книг з теми "Social Science"

1

Wright, James D. "Popular Science and Social Science." In Social Problems, Social Issues, Social Science, 84–97. New Brunswick : Transaction Publishers, [2016] | Collection of papers originally published in the journal Society.: Routledge, 2017. http://dx.doi.org/10.4324/9781315129716-4.

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2

Biletzki, Anat. "Social Science." In (Over)Interpreting Wittgenstein, 145–61. Dordrecht: Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-007-0822-8_10.

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3

John, Staddon. "Social Science." In Scientific Method, 52–69. New York, NY : Routledge, 2018.: Routledge, 2017. http://dx.doi.org/10.4324/9781315100708-4.

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4

John, Staddon. "Social Science." In Scientific Method, 70–90. New York, NY : Routledge, 2018.: Routledge, 2017. http://dx.doi.org/10.4324/9781315100708-5.

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5

Staddon, John. "Social Science." In Scientific Method, 103–10. 2nd ed. New York: Routledge, 2024. http://dx.doi.org/10.4324/9781032683874-9.

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6

Staddon, John. "Social Science." In Scientific Method, 69–88. 2nd ed. New York: Routledge, 2024. http://dx.doi.org/10.4324/9781032683874-6.

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7

Shattock, Joanne. "Social Science." In The Selected Works of Margaret Oliphant, Part I Volume 1, 221–30. London: Routledge, 2024. http://dx.doi.org/10.4324/9781003513155-24.

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8

Solo, Robert A. "Social Science, Policy Science." In The Philosophy of Science, and Economics, 69–84. London: Palgrave Macmillan UK, 1991. http://dx.doi.org/10.1007/978-1-349-12224-0_4.

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9

Albert, Alexandra, Bálint Balázs, Eglė Butkevičienė, Katja Mayer, and Josep Perelló. "Citizen Social Science: New and Established Approaches to Participation in Social Research." In The Science of Citizen Science, 119–38. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-58278-4_7.

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AbstractThis chapter explores the ways in which the roles of citizens and researchers play out in the social sciences. This is expressed by numerous overlapping and related terms, such as co-production and participatory action research, to name but two, and by the different social topics that citizen social science draws attention to. The key question this chapter seeks to explore is what does naming citizen social science as such bring to the fields of citizen science and the social sciences? The chapter explores the different epistemic foundations of citizen social science and outlines the development and provenance of citizen social science in its broadest sense, reflecting on how it is currently practised. It draws on different examples from the experiences and work of the authors and notes the boundaries and overlaps with citizen science. The chapter also highlights some of the key issues that citizen social science gives rise to, emphasising that while citizen social science is a relatively new term, its underlying approaches and epistemic foundations are at least partially established in the social sciences.

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10

Wright, James D. "Social Science in Review." In Social Problems, Social Issues, Social Science, 264–93. New Brunswick : Transaction Publishers, [2016] | Collection of papers originally published in the journal Society.: Routledge, 2017. http://dx.doi.org/10.4324/9781315129716-11.

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Тези доповідей конференцій з теми "Social Science"

1

Parigi, Paolo. "Computational social science." In WebSci '16: ACM Web Science Conference. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2908131.2908138.

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2

Watts, Duncan. "Computational Social Science." In KDD '16: The 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2939672.2945366.

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3

Counts, Scott, Munmun De Choudhury, Jana Diesner, Eric Gilbert, Marta Gonzalez, Brian Keegan, Mor Naaman, and Hanna Wallach. "Computational social science." In the companion publication of the 17th ACM conference. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2556420.2556849.

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4

Hagen, Loni. "Teaching Data Science to Social Sciences and Humanities Students." In dg.o '20: The 21st Annual International Conference on Digital Government Research. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3396956.3396968.

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5

El Makkouk, Mazen, Cláudia Daniele DE SOUZA, and Carlos Suárez Balseiro. "Adding humanities and social science publications to Wikidata: a contribution to the Open Science movement." In 27th International Conference on Science, Technology and Innovation Indicators (STI 2023). International Conference on Science, Technology and Innovation Indicators, 2023. http://dx.doi.org/10.55835/643c5781dc7d38a4a1546e27.

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Анотація:

This is a case study which describes and evaluates the process of creating Wikidata items for academic journals and articles published by the University of Puerto Rico in the humanities and social sciences, as part of an open science initiative. It suggests preliminary steps that can be taken to improve indexing and to register local geographic, disciplinary, and cultural contexts for humanities and social science journals on Wikidata. Finally, argues that these steps can promote a different way of evaluating scholarship in these fields, more appropriate to the humanities and social sciences but nevertheless promoting scholarly cooperation in a spirit consistent with the ethos of open science as perceived by the author.

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6

Taşer, Seyit. "SOCIAL SCIENCES IN TEACHING BENEFIT FROM THE NATUREL SCIENCE- EXAMPLES OF HISTORY OF SCIENCE." In 3rd Teaching & Education Conference, Barcelona. International Institute of Social and Economic Sciences, 2016. http://dx.doi.org/10.20472/tec.2016.003.020.

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7

Ivanjko, Tomislav, Zoran Horvat, and Sofija Ajanović. "CITIZEN SCIENCE IN SOCIAL SCIENCES AND HUMANITIES – TRENDS AND PERSPECTIVES." In 16th annual International Conference of Education, Research and Innovation. IATED, 2023. http://dx.doi.org/10.21125/iceri.2023.0642.

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8

Williams, Titus, Gregory Alexander, and Wendy Setlalentoa. "SOCIAL SCIENCE STUDENT TEACHERS’ AWARENESS OF THE INTERTWINESS OF SOCIAL SCIENCE AND SOCIAL JUSTICE IN MULTICULTURAL SCHOOL SETTINGS." In International Conference on Education and New Developments. inScience Press, 2021. http://dx.doi.org/10.36315/2021end037.

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This qualitative study is an exploration of final year Social Science education students awareness of the intertwined nature of Social Science as a subject and the role of social justice in the classroom of a democratic South Africa. This study finds that South African Social Science teachers interpret or experience the teaching of Social Science in various ways. In the South African transitional justice environment, Social Science education had to take into account the legacies of the apartheid-era schooling system and the official history narrative that contributed to conflict in South Africa. Throughout the world, issues of social justice and equity are becoming a significant part of everyday discourse in education and some of these themes are part of the Social Science curriculum. Through a qualitative research methodology, data was gathered from Focus Group Discussion (FGD) sessions with three groups of five teacher education students in two of the groups and the third having ten participants from the same race, in their final year, specializing in Social Science teaching. The data obtained were categorised and analysed in terms of the student teacher’s awareness of the intertwined nature of Social Science and social justice education. The results of the study have revealed that participants had a penchant for the subject Social Science because it assisted them to have a better understanding of social justice and the unequal society they live in; an awareness of social ills, and the challenges of people. Participants identified social justice characteristics within Social Science and relate to some extent while they were teaching the subject, certain themes within the Social Science curriculum. Findings suggest that the subject Social Science provides a perspective as to why social injustice and inequality are so prevalent in South Africa and in some parts of the world. Social Science content in its current form and South African context, emanates from events and activities that took place in communities and in the broader society, thus the linkage to social justice education. This study recommends different approaches to infuse social justice considerations Social Science; one being an empathetic approach – introducing activities to assist learners in viewing an issue from someone else’s perspective, particularly when issues of prejudice or discrimination against a particular group arise, or if the issue is remote from learners’ lives.

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9

Palladino, Anthony, Elisa J. Bienenstock, Christopher A. George, and Kendra E. Moore. "Big open-source social science: capabilities and methodology for automating social science analytics." In Next-Generation Analyst VI, edited by James Llinas and Timothy P. Hanratty. SPIE, 2018. http://dx.doi.org/10.1117/12.2306500.

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10

Conway, Drew. "Data science through the lens of social science." In KDD '14: The 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2623330.2630824.

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Звіти організацій з теми "Social Science"

1

Davies, Philip. Review of FSA Social Science. Food Standards Agency, August 2023. http://dx.doi.org/10.46756/sci.fsa.qfy428.

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This review has attempted to assess the contribution that the FSA social science team makes to the FSA and its mission, and to identify what it does well, where there may be need for improvement, and what might be the direction of future learning and professional development.

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González-Cabán, Armando, Richard W. Haynes, Sarah McCaffrey, Evan Mercer, and Alan Watson. Fire social science research–selected highlights. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 2007. http://dx.doi.org/10.2737/pnw-gtr-736.

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3

Fisman, Raymond, Jing Shi, Yongxiang Wang, and Rong Xu. Social Ties and Favoritism in Chinese Science. Cambridge, MA: National Bureau of Economic Research, February 2017. http://dx.doi.org/10.3386/w23130.

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4

Johnston, Kim A., and Amanda T. Beatson. Healthy Waterways Social Science Research Report 2016. Queensland, Australia: Queensland University of Technology, January 2016. http://dx.doi.org/10.5204/rep.eprints.105457.

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5

Johnston, Kim A., and Amanda T. Beatson. Healthy Waterways Social Science Research Report 2015. Queensland, Australia: Queensland University of Technology, January 2015. http://dx.doi.org/10.5204/rep.eprints.93606.

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6

Landis, Ronald. Regression Analysis for Social and Health Science. Instats Inc., 2023. http://dx.doi.org/10.61700/me4ohse6jsdoy469.

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This comprehensive 2-day workshop will equip PhD students, professors, and professional researchers with the knowledge and skills needed to effectively use multiple regression analysis in their research. Participants will gain a deep understanding of multiple regression, learn how to use R, Excel, and Jamovi for analysis, interpret and report results, handle missing data, and enhance their research capabilities. An official Instats certificate of completion and 2 ECTS Equivalent points are provided at the conclusion of the seminar.

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7

Duca, Daniela, and Katie Metzler. The Ecosystem of Technologies for Social Science Research. SAGE Publishing, November 2019. http://dx.doi.org/10.4135/wp191101.

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8

Westphal, Lynne M., Cristy Watkins, Paul H. Gobster, Liam Heneghan, Kristen Ross, Laurel Ross, Madeleine Tudor, et al. Social Science Methods Used in the RESTORE Project. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station, 2014. http://dx.doi.org/10.2737/nrs-gtr-138.

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9

Benjamin, Daniel, David Cesarini, Patrick Turley, and Alexander Strudwick Young. Social-Science Genomics: Progress, Challenges, and Future Directions. Cambridge, MA: National Bureau of Economic Research, May 2024. http://dx.doi.org/10.3386/w32404.

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10

Martens, Bryce. Data Science Impact on Social Welfare Program Administration. Ames (Iowa): Iowa State University, December 2022. http://dx.doi.org/10.31274/cc-20240624-480.

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