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Regular version of the site
Of all publications in the section: 117
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Article
Настина Е. А. Социология: методология, методы, математическое моделирование. 2020. № 50-51. С. 7-36.
Added: Jun 17, 2021
Article
Стребков Д. О. Социология: методология, методы, математическое моделирование. 2010. № 31. С. 135-161.

Интернет-опрос, онлайн-опрос, репрезентативность и смещения выборки в онлайн-исследованиях, фрилансеры, контроль за ходом опроса, коммуникация в Интернете

Added: Oct 21, 2012
Article
Савинская О. Б., Истомина А. Г. Социология: методология, методы, математическое моделирование. 2015. № 41. С. 142-149.

This note describes the results of the roundtable discussion on mixed methods research (MMR) held in HSE (November 26, 2015).The conceptual framework of MMR, i.e. research that is characterized by mixing of quantitative and qualitative data collection and analysis methods, was the main focus of the discussion. The key topics were: the practices of using different terms to refer to MMR studies in the Russian sociology discourse; theoretical basis of combining quantitative and qualitative research methods; justification of the “mixed strategy” concept as the most relevant to refer to MMR in Russian language; problems of describing MMR results and interpreting data stemming from different data sources.

Added: Sep 15, 2016
Article
Абрамова Н. В. Социология: методология, методы, математическое моделирование. 2006. № 23. С. 83-100.
Added: Mar 24, 2016
Article
Абрамов Р. Н. Социология: методология, методы, математическое моделирование. 2019. № 48. С. 83-112.

The digitalization of sociological surveys affects all stages of their organization. Recruiting respondents through social networks is one of the new opportunities for organizing opinion polls. This article summarizes experience in this area and gives a description of the practical experience of recruiting a target sample using social networks. Researchers use the potential of recruiting respondents in social networks to work with hidden populations that are difficult to achieve using conventional methods of invitation to participate or if the survey is conducted on sensitive topics. This recruitment method has limitations of methodical and thematic nature.

Added: Apr 6, 2018
Article
Тенишева К. А., Савельева С. С., Александров Д. А. Социология: методология, методы, математическое моделирование. 2018. № 46. С. 44-84.

In the article we suggest a method for analyzing situations of choice, which is novel for sociology - the method of conditional decision trees. We describe the logic of the method, applying it to the case of parental choice of school in two urban districts of Saint-Petersburg. We show that decision trees work well for detecting groups that follow different decision making strategies. This can be an efficient tool for modeling and interpretation of the logic of choice. The method outperforms the traditional modeling by means of logistic regression, as it allows for assessing homogeneity of preferences (choices) of the groups detected, instead of simply finding the key factors related to choice. We recommend combining regression analysis with decision trees modeling in all kinds of academic and applied research studying complicated choices.

Added: Oct 19, 2018
Article
Волченко О. В., Широканова А. А. Социология: методология, методы, математическое моделирование. 2016. № 43. С. 7-62.

The paper deals with multilevel regression modelling (MLM) as a method preferred to the ordinary least-squares regression in the analysis of comparative data with hierarchical data structure. We present substantive reasons (contextual sources of heterogeneity, causal heterogeneity, and generalisability of results) and statistical reasons (obtaining more precise and reliable estimates) for multilevel modelling. We also provide an overview of MLM implementation in several statistical packages. Using the cross-national World Values Survey (WVS) data, we outline a step-by-step procedure for building and fitting a two-level linear regression model of generalized trust on educational attainment levels (the “null” model, the fixed-intercept model, the random-intercept model, the random-intercept random-slope model, the model with a country-level predictor, and the cross-level interaction model). Then we describe and compare existing goodness-of-fit measures for MLM (AIC, BIC, maximum likelihood functions, and pseudo-R2). We also demonstrate robustness check techniques for multilevel models (visualization, Cook’s distance, and DFBETAs). In the final section, we overview alternative approaches to multilevel modelling when dealing with hierarchical data (cluster robust standard errors, generalized estimating equations, country fixed effects, country means, and aggregation) as currently practiced in comparative cross-national social science research. The replicable R code is attached.

Added: Aug 9, 2017
Article
Девятко И. Ф. Социология: методология, методы, математическое моделирование. 2007. № 25. С. 5-21.
Added: Nov 5, 2009
Article
Зангиева И. К. Социология: методология, методы, математическое моделирование. 2011. Т. 33. С. 28-56.
Added: Sep 15, 2012
Article
Стребкова О. Н., Понарин Э. Д., Костенко В. В. Социология: методология, методы, математическое моделирование. 2017. № 44. С. 7-36.
Added: Dec 29, 2017
Article
Давыдов С. Г., Логунова О. С. Социология: методология, методы, математическое моделирование. 2015. № 41. С. 120-141.
Added: Sep 20, 2016
Article
Оберемко О. А. Социология: методология, методы, математическое моделирование. 2010. № 31. С. 46-63.
Added: Mar 25, 2011
Article
Гаврилов К. А., Бутынко М. В. Социология: методология, методы, математическое моделирование. 2019. № 48. С. 113-142.

The article presents the experience of adapting the methodology of the “psychometric paradigm” of risk perception (P. Slovic, B. Fischhoff, S. Lichtenstein and others) for the situation of an online survey with little incentives for participants. The initial methodology involves assessing several dozens of risks by a fixed set of characteristics, and it requires significant time (at least an hour), usually unacceptable for online surveys. We propose to use the split questionnaire design, where the respondent assesses only a part of the risk list, which significantly reduces the burden on the respondent. The results obtained from the “split” questionnaire (N = 220), in general, correspond to the data of an online survey on a student sample (N = 91): although there are differences in risk “profiles”, the identified factors for the perception of dangerous objects are very similar, and the positions of risks in two-dimensional space are quite close. Despite the disadvantages of using a “split” questionnaire (the need for a larger number of respondents, difficulties in analyzing data at the individual level), the article cautiously recommends using this format in online surveys.

Added: Dec 8, 2019
Article
Толстова Ю. Н. Социология: методология, методы, математическое моделирование. 2015. № 40. С. 7-31.
Added: Mar 13, 2016
Article
Моисеев С. П. Социология: методология, методы, математическое моделирование. 2016. № 42. С. 61-83.
Added: Oct 16, 2016
Article
Толстова Ю. Н. Социология: методология, методы, математическое моделирование. 1996. № 7. С. 62-80.
Added: Nov 26, 2010
Article
Сафонова М. А., Винер Б. Е. Социология: методология, методы, математическое моделирование. 2013. № 36. С. 140-176.
Added: Oct 16, 2013
Article
Даудрих Н. И. Социология: методология, методы, математическое моделирование. 2000. № 12.
Added: Oct 9, 2010
Article
Ибарра П., Адорьян М. Социология: методология, методы, математическое моделирование. 2019. № 48. С. 143-182.

This overview of social constructionism begins with a consideration of the influential work of Malcolm Spector and John I. Kitsuse, whose book, “Constructing Social Problems”, inspired a wide variety of studies addressing how social problems are “constructed”. Ensuing epistemological and methodological controversies are discussed, and three key scholarly works are reviewed for the insights they offer into exemplary analytic practice in a constructionist vein. The exemplars pivot around the notion that “understanding understandings” is essential to executing constructionist analysis and does not entail subscribing to reified conceptions of objective conditions. The chapter concludes by discussing three promising directions for extending the constructionist purview, namely, through the study of (1) cyberspace (including social media) as an emerging but essential venue for the construction of social problems; (2) claims-making in national contexts beyond the Anglo Global North, especially in countries that challenge the liberal democratic assumptions upon which constructionist scholarship usually rests; and (3) a broadened, more quotidian conception of the social spaces and forms through which social problems-related expression is advanced.

Added: May 21, 2020
Article
Ибарра П., Адорьян М. Социология: методология, методы, математическое моделирование. 2019. Т. 49. С. 161-181.
Added: May 18, 2021
Article
Мавлетова А. М. Социология: методология, методы, математическое моделирование. 2010. № 31. С. 115-134.
Added: Oct 21, 2012