Teaching stats: A crisis in Irish sociology?

2015 ◽  
Vol 24 (1) ◽  
pp. 102-111
Author(s):  
Carmel Hannan
Keyword(s):  
Big Data ◽  
Social Science ◽  
Mixed Methods Research ◽  
Quantitative Methods ◽  
Social Science Research ◽  
Science Research ◽  
Undergraduate Level ◽  
Sociology Departments ◽  
The Uk ◽  
Research Councils

There is now a lack of quantitative capacity among practitioners and teachers in sociology in Ireland. Yet interest in the value of quantitative methods among governments, funding organisations and society in general are on the increase. Social science research councils and funders in other countries, notably the UK, have realised there is a problem and are now attempting to remedy this through increased funding for the recruitment of quantitatively trained academics for example, Q-Step. The paper examines a number of developments notably Big Data, increases in transdisciplinary research and developments in mixed methods research which, it is argued, underline the need for more and better quantitative methods teaching in sociology. The paper calls for sociology departments to re-think their curricula and actively promote the teaching of a range of methods at the undergraduate level.

scholarly journals Not teaching what we practice: undergraduate conservation training at UK universities lacks interdisciplinarity

2020 ◽  
pp. 1-6
Author(s):  
Charlie J Gardner
Keyword(s):  
Social Science ◽  
Text Analysis ◽  
Social Science Research ◽  
Science Research ◽  
Conservation Education ◽  
Interdisciplinary Education ◽  
Science Content ◽  
Undergraduate Level ◽  
The Uk ◽  
Science Training

Summary The practice and science of conservation have become increasingly interdisciplinary, and it is widely acknowledged that conservation training in higher education institutions should embrace interdisciplinarity in order to prepare students to address real-world conservation problems. However, there is little information on the extent to which conservation education at the undergraduate level meets this objective. I carried out a systematic search of undergraduate conservation degree programmes in the UK and conducted a simple text analysis of module descriptions to quantify the extent to which they provide social science training. I found 47 programmes, of which 29 provided module descriptions. Modules containing social science content ranged from 3.8% to 52.2% of modules across programmes, but only 55.2% of programmes offered a social-focused conservation module, and only one programme offered a module in social science research methods. On average, almost half of the modules offered (46.2%) comprised biology and ecology modules with no conservation focus, and 17.9% comprised skills-based modules (research and vocational skills). Conservation-focused modules comprised a mean of only 22.5% of modules. These results show that undergraduate conservation teaching in the UK is still largely biocentric and is failing to deliver the interdisciplinary education that is widely called for.

scholarly journals The role of administrative data in the big data revolution in social science research

2016 ◽  
Vol 59 ◽  
pp. 1-12 ◽  
Author(s):  
Roxanne Connelly ◽  
Christopher J. Playford ◽  
Vernon Gayle ◽  
Chris Dibben
Keyword(s):  
Big Data ◽  
Social Science ◽  
Administrative Data ◽  
Social Science Research ◽  
Science Research

scholarly journals Affective economy of national-populist images: Investigating national and transnational online networks through visual big data

2019 ◽  
Vol 22 (5) ◽  
pp. 770-792
Author(s):  
Jenni Hokka ◽  
Matti Nelimarkka
Keyword(s):  
Social Media ◽  
Big Data ◽  
Quantitative Methods ◽  
Social Science Research ◽  
Historical Analysis ◽  
Science Research ◽  
Online Networks ◽  
Qualitative And Quantitative Methods ◽  
Computational Data

In our article, we investigate the affective economy of national-populist image circulation on Facebook. This is highly relevant, since social media has been an essential area for the spread of national-populist ideology. In our research, we analyse image circulation as affective practice, combining qualitative and quantitative methods. We use computational data analysis methods to examine visual big data: image fingerprints and reverse image search engines to track down the routes of thousands of circulated images as well as make discourse-historical analysis on the images that have gained most attention among supporters. Our research demonstrates that these existing tools allow social science research to make theory-solid approaches to understand the role of image circulation in creating and sustaining national and transnational networks on social media, and show how national-populist thinking is spread through images that catalyse and mobilise affects – fear, anger and resentment – thus creating an effective affective economy.

Trade-Offs, Limitations, and Promises of Big Data in Social Science Research

2014 ◽  
Vol 31 (4) ◽  
pp. 331-338 ◽  
Author(s):  
Patricia White ◽  
R. Saylor Breckenridge
Keyword(s):  
Big Data ◽  
Social Science ◽  
Social Science Research ◽  
Science Research ◽  
Trade Offs

scholarly journals Empowering Social Science Research in the Big-Data Era: Addressing Quantyphobia in IR Researches

2019 ◽  
Vol 2 (2) ◽  
pp. 259
Author(s):  
Farizal Mohd Razalli
Keyword(s):  
Big Data ◽  
Quantitative Methods ◽  
International Politics ◽  
Research Output ◽  
Social Science Research ◽  
Science Research ◽  
Global Changes ◽  
Intellectual Community ◽  
Mechanical Field ◽  
Research Outcome

This paper tries to explore the employment of quantitative approach in political researches focusing on international relations (IR) or international politics. A debate emerged in the90s on whether IR or the field of international politics should be driven by quantitative(positivistic) approach at the expense of qualitative (interpretivist) approach. The debate then expanded to explicitly argue for an increased use of formal methods that are mathematically-based to study IR phenomena. It triggered then a quick reaction fromhardcore IR specialists who warned against mathematizing IR for fear of turning the field into a mechanical field that crunches numbers. Such a fear is further substantiated by theobservation that many quantitative works in IR have moved farther away from developing theory to testing hypotheses. Some scholars have even suggested that it is epistemologicallyrealism vs. instrumentalism; something that is unsurprising given the dominance of realism inIR for many years. This paper does not suggest that heavy emphasis on qualitative approach leads to a inferior research output. However, it does suggest an transformative incapability among IR scholars to accommodate to contemporary global changes. The big-data analyticshave affected the intellectual community of late with the influx of data. These data are bothqualitative and quantitative. Nonetheless, analyzing them requires one to be familiar with quantitative methods lest one risks not being able to offer a research outcome that is not only sound in its argumentation but also robust in its analytical logic. Furthermore, with so much data on the social media, it is almost unthinkable for meaningful interpretation tobe made without even the simplest descriptive statistical methods. The key findings revealthat in ensuring its relevance, international political researches have to start adapting to the contemporary changes by building new capability apart from upscaling existing capacity.

scholarly journals Big data method and its application in innovation education research

2021 ◽  
Vol 290 ◽  
pp. 03022
Author(s):  
Yankui Song ◽  
Chuijiao Jie ◽  
Zhijin Xu
Keyword(s):  
Big Data ◽  
Social Science ◽  
Timing Analysis ◽  
Social Science Research ◽  
Science Research ◽  
Development Trend ◽  
Scientific Basis ◽  
Source Analysis ◽  
Knowledge Mapping ◽  
Big Data Technology

Big data technology is a new stage of information development. In recent years, it has been widely used in many fields, especially in social science research. This paper analyzes the development status and significance of the combination of big data technology and social science research, on the basis of summarizing and combing the concept of big data and its important role. Taking the application of big data method in the research of innovation education as an example, this paper makes a series of visualization analysis with Citespace software on the related literature with the theme of “big data and innovation education” collected by CNKI, such as annual analysis, literature source analysis, co-occurrence analysis of authors, organization analysis, keyword clustering analysis and keyword timing analysis. This paper also draws the corresponding knowledge mapping, clarifies its research status, hot spots and development trend, and provides scientific basis for the research of innovation education. Thus the paper believes that the research on big data and innovation education needs to strengthen interdisciplinary communication and cooperation, refine and deepen the research theme and content.

Quality of Publication in International Context

2017 ◽  
Author(s):  
N. Lalitha ◽  
Amrita Ghatak
Keyword(s):  
Social Sciences ◽  
Social Science ◽  
Social Science Research ◽  
Science Research ◽  
Comparative Performance ◽  
International Context ◽  
Global Context ◽  
The Status ◽  
The Usa ◽  
The Uk

This chapter analyses the status of India’s social science research (SSR) publications in global context. The outputs chosen to assess India’s comparative performance is the articles written and published by Indians in the field of social sciences either individually or in collaboration with researchers outside India. The study analysed journal articles published during 2008–14 drawn from Scopus database to examine the publication status of India in social sciences in an international context. The study found that the six-year period, 2009–14, India consistently ranks among the top 15 countries in the world. Discipline-wise analysis shows that the share of pure social science articles was significant but is declining. Of the total 30938 articles, 28 per cent are published with international collaboration. The USA and the UK contribute 52 per cent of total international collaborations.

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