Везде
PROBLEMS AND PROSPECTS OF RESEARCH BASED ON BIG DATA (ON THE EXAMPLE OF THE SOCIOLOGY OF LAW)
Table of contents
Annotation Estimate Publication content
References Comments
Share
QR
Metrics
PROBLEMS AND PROSPECTS OF RESEARCH BASED ON BIG DATA (ON THE EXAMPLE OF THE SOCIOLOGY OF LAW)
Annotation
PII
S0132-16250000375-8-
Publication type
Article
Status
Published
Authors
Dmitry Skugarevsky  Kirill Titaev Vadim Volkov
Edition
Volume 381 Issue 1
Pages
48-58
Abstract
The article describes the phenomenon of Big Data and the potential of sociology in working with new sources and types of data. The parameters of “big data " are described, and examples describing the complexity and features of working with them are given. It is shown that some data that sociologists have been working with for a long time (state and industry statistics) in a modern (disaggregated) form, create the same opportunities and problems for the analyst as “big data". An example of sociological work with big data is analyzed on the example of research of statistical cards on criminal defendants. The research logic caused by the appearance of large data sets is described. It focuses on interpreting the meaning of existing data. The article ends with a critique of “big data” and discusses the feasibility of using this concept as an example of an economy that has experienced a similar “data revolution".
Keywords
quantitative research; methodology of sociological research; Big Data; sociology of law
Date of publication
01.01.2016
Number of purchasers
1
Views
466
Readers community rating
0.0 (0 votes)
Previous versions
S0132-16250000375-8-1 Дата внесения правок в статью - 06.10.2020
Cite Download pdf

References



Additional sources and materials

Batygin G.S. Lektsii po metodologii sotsiologicheskikh issledovanij. M.: RUDN, 2008.


Volkov V.V. Vliyanie sotsial'nogo statusa podsudimogo na reshenie suda // Zhurnal sotsiologii i sotsial'noj antropologii. 2014. № 4. S. 62–85.


Kriminal'naya statistika: mekhanizmy formirovaniya, prichiny iskazheniya, puti reformirovaniya. Issledovatel'skij otchet / M. Shklyaruk, D. Skugarevskij, A. Dmitrieva, I. Skifskij, I. Begtin. SPb.: Institut problem pravoprimeneniya pri Evropejskom universitete v Sankt-Peterburge; M.: Norma, 2015.


Skugarevskij D.A. (red.) Ugolovnaya yustitsiya v Rossii v 2009 g.: kompleksnyj analiz sudebnoj statistiki. SPb.: Institut problem pravoprimeneniya pri Evropejskom universitete v Sankt-Peterburge; M.: Statut, 2014.


Titaev K.D. Kak sudy prinimayut resheniya: issledovanie vliyaniya vnepravovykh faktorov na rossijskie sudy // Ehkonomicheskaya sotsiologiya. 2011. № 4. S. 122–125.


Tsyplakov A. Mini-slovar' angloyazychnykh ehkonometricheskikh terminov. Ch. 1 // Kvantil'. 2007. № 3. S. 67–72.


Chetverikova I.V. Rol' sem'i, professional'noj kar'ery i pola podsudimykh pri vynesenii prigovorov rossijskimi sud'yami // Zhurnal sotsiologii i sotsial'noj antropologii. 2014. № 4. S. 101–123.


Angrist J., Pischke J.-S. The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics // Journal of Economic Perspectives. 2010. № 24(2). R. 3–30.


Anderson C. The end of theory // Wired magazine. 2008. № 16(7). URL: http: / /archive.wired.com / science /discoveries /magazine /16–07 /pb_theory (data obrascheniya: 13.05.2015).


Banerjee A.V., Duflo E. Poor economics: A radical rethinking of the way to fight global poverty. Chicago: PublicAffairs, 2011.


Banerjee A., Duflo E., Glennerster R., Kinnan C. The miracle of microfinance? Evidence from a randomized evaluation // CEPR Discussion Papers. 2013. №. 9437. R. 22–53.


Chan J., Tobias J. Priors and posterior computation in linear endogenous variable models with imperfect instruments // Journal of Applied Econometrics, forthcoming. June /July 2015. Vol. 30, Issue 4. R. 650–674.


Efron B. Maximum likelihood and decision theory // Annals of Statistics. 1982. № 10(2). R. 340–356.


Kitchin R. Big Data, new epistemologies and paradigm shifts // Big Data & Society. 2014. April – June. 1–12. URL: http: / /bds.sagepub.com /content /spbds /1 /1 /2053951714528481.full.pdf (data obrascheniya: 13.05.2015).


Kitchin R. Big data and human geography: Opportunities, challenges and risks // Dialogues in Human Geography. 2013. № 3(3). R. 262–267.


Laney D. 3D Data Management: Controlling Data Volume, Velocity and Variety // Application Delivery Strategies. META Group Report, 06.02.2001. URL: http: / /blogs.gartner.com /doug-laney / files /2012 /01 /ad949–3D-Data-


Management-Controlling-Data-Volume-Velocity-and-Variety.pdf (data obrascheniya: 13.05.2015).


Sala-I-Martin X. I Just Ran Two Million Regressions // American Economic Review: Papers and Proceedings. 1997. № 87(2). № 178–183.


Volkov V. Socioeconomic Status and Sentencing Disparities: Evidence from Russia’s Criminal Courts – The European University at St.-Petersburg, The Institute for the Rule of Law. Working paper IRL-01 /2014.


World Bank. Open data for economic growth in Russia. // World Bank Transport & ICT Global Practice Note Series. 2014. July.

Comments

No posts found

Write a review
Translate