scholarly journals The Impact of Computer Networking on the Social Science Data Library

1978 ◽  
Vol 2 (1) ◽  
pp. 3
Author(s):  
Alice Robbin
Keyword(s):  
Social Science ◽  
Computer Networking ◽  
Science Data ◽  
The Social ◽  
Social Science Data ◽  
The Impact ◽  
Data Library

The Impact of Computer Networking on the Social Science Data Library

scholarly journals Integrating the social sciences in epidemic preparedness and response: A strategic framework to strengthen capacities and improve Global Health security

2020 ◽  
Vol 16 (1) ◽  
Author(s):  
Kevin Louis Bardosh ◽  
Daniel H. de Vries ◽  
Sharon Abramowitz ◽  
Adama Thorlie ◽  
Lianne Cremers ◽  
...  
Keyword(s):  
Social Sciences ◽  
Social Science ◽  
Capacity Building ◽  
Core Competencies ◽  
Institutional Development ◽  
Science Data ◽  
Social Scientists ◽  
Strategic Framework ◽  
The Social ◽  
The Impact

Abstract Background The importance of integrating the social sciences in epidemic preparedness and response has become a common feature of infectious disease policy and practice debates. However to date, this integration remains inadequate, fragmented and under-funded, with limited reach and small initial investments. Based on data collected prior to the COVID-19 pandemic, in this paper we analysed the variety of knowledge, infrastructure and funding gaps that hinder the full integration of the social sciences in epidemics and present a strategic framework for addressing them. Methods Senior social scientists with expertise in public health emergencies facilitated expert deliberations, and conducted 75 key informant interviews, a consultation with 20 expert social scientists from Africa, Asia and Europe, 2 focus groups and a literature review of 128 identified high-priority peer reviewed articles. We also analysed 56 interviews from the Ebola 100 project, collected just after the West African Ebola epidemic. Analysis was conducted on gaps and recommendations. These were inductively classified according to various themes during two group prioritization exercises. The project was conducted between February and May 2019. Findings from the report were used to inform strategic prioritization of global investments in social science capacities for health emergencies. Findings Our analysis consolidated 12 knowledge and infrastructure gaps and 38 recommendations from an initial list of 600 gaps and 220 recommendations. In developing our framework, we clustered these into three areas: 1) Recommendations to improve core social science response capacities, including investments in: human resources within response agencies; the creation of social science data analysis capacities at field and global level; mechanisms for operationalizing knowledge; and a set of rapid deployment infrastructures; 2) Recommendations to strengthen applied and basic social sciences, including the need to: better define the social science agenda and core competencies; support innovative interdisciplinary science; make concerted investments in developing field ready tools and building the evidence-base; and develop codes of conduct; and 3) Recommendations for a supportive social science ecosystem, including: the essential foundational investments in institutional development; training and capacity building; awareness-raising activities with allied disciplines; and lastly, support for a community of practice. Interpretation Comprehensively integrating social science into the epidemic preparedness and response architecture demands multifaceted investments on par with allied disciplines, such as epidemiology and virology. Building core capacities and competencies should occur at multiple levels, grounded in country-led capacity building. Social science should not be a parallel system, nor should it be “siloed” into risk communication and community engagement. Rather, it should be integrated across existing systems and networks, and deploy interdisciplinary knowledge “transversally” across all preparedness and response sectors and pillars. Future work should update this framework to account for the impact of the COVID-19 pandemic on the institutional landscape.

scholarly journals The Social Science Data Archive in Slovenia

2001 ◽  
Vol 25 (2) ◽  
pp. 24
Author(s):  
Janez Stebe ◽  
Irena Vipavc
Keyword(s):  
Social Science ◽  
Data Archive ◽  
Science Data ◽  
The Social ◽  
Social Science Data

The Social Science Data Archive in Slovenia

The Haitun dichotomy and the relevance of Bradford's law

1984 ◽  
Vol 8 (1) ◽  
pp. 19-24 ◽  
Author(s):  
B.C. Brookes
Keyword(s):  
Social Sciences ◽  
Statistical Theory ◽  
Social Science ◽  
Critical Review ◽  
Science Data ◽  
Bradford’S Law ◽  
The Social ◽  
Social Science Data

In a critical review of all the empirical laws of bibliometrics and scientometrics, the Russian statistician S.D. Haitun has shown that the application of modern statistical theory to social science data is 'inadmissible', i.e. it 'does not work'. Haitun thus points to the need to develop a wholly new statistical theory for the social sciences in general and for informetrics in particular. This paper discusses the implications of Haitun's work and explains why the older Bradford law still has an important role to play in the development of a new theory.

scholarly journals The matter of meta in research data management: Introducing the CESSDA Metadata Office Project

2020 ◽  
Vol 44 (3) ◽  
Author(s):  
André Förster ◽  
Kerrin Borschewski ◽  
Sharon Bolton ◽  
Taina Jääskeläinen
Keyword(s):  
Social Science ◽  
Data Management ◽  
Service Providers ◽  
Research Data ◽  
Science Data ◽  
Research Data Management ◽  
Data Archives ◽  
The Social ◽  
The Impact ◽  
Science And Research

Accompanying the growing importance of research data management, the provision and maintenance of metadata – understood as data about (research) data – have obtained a key role in contextualizing, understanding, and preserving research data. Acknowledging the importance of metadata in the social sciences, the Consortium of European Social Science Data Archives started the Metadata Office project in 2019. This project report presents the various activities of the Metadata Office (MDO). Metadata models, schema, controlled vocabularies and thesauri are covered, including the MDO’s collaboration with the DDI Alliance on multilingual translations of DDI vocabularies for CESSDA Service Providers. The report also summarizes the communication, training and advice provided by MDO, including DDI use across CESSDA, illustrates the impact of the project for the social science and research data management community, and offers an outline regarding future plans of the project.

scholarly journals Guidelines on the Provision and Handling of Research Data in Sociology

2020 ◽  
Author(s):  
Academy of Sociology
Keyword(s):  
Social Sciences ◽  
Social Science ◽  
Research Data ◽  
Professional Association ◽  
Science Data ◽  
The Social ◽  
Social Science Data

With these guidelines the Academy of Sociology (a German professional association) gives recommendations on how social science data could be made open. The aim is to make the Social Sciences more open.

Social Science Data and the Courts

1976 ◽  
Vol 5 (5) ◽  
pp. 11-13
Author(s):  
PATRICIA E. STIVERS
Keyword(s):  
Social Science ◽  
Science Data ◽  
Social Science Data

scholarly journals Uncomfortable Decisions

2022 ◽  
Author(s):  
Paul Bloom ◽  
Laurie Paul
Keyword(s):  
Decision Making ◽  
Social Science ◽  
Career Change ◽  
Social Science Research ◽  
Science Research ◽  
Science Data ◽  
Decision Making Processes ◽  
Social Science Data ◽  
Personal Decision ◽  
Algorithmic Process

Some decision-making processes are uncomfortable. Many of us do not like to make significant decisions, such as whether to have a child, solely based on social science research. We do not like to choose randomly, even in cases where flipping a coin is plainly the wisest choice. We are often reluctant to defer to another person, even if we believe that the other person is wiser, and have similar reservations about appealing to powerful algorithms. And, while we are comfortable with considering and weighing different options, there is something strange about deciding solely on a purely algorithmic process, even one that takes place in our own heads.What is the source of our discomfort? We do not present a decisive theory here—and, indeed, the authors have clashing views over some of these issues—but we lay out the arguments for two (consistent) explanations. The first is that such impersonal decision-making processes are felt to be a threat to our autonomy. In all of the examples above, it is not you who is making the decision, it is someone or something else. This is to be contrasted with personal decision-making, where, to put it colloquially, you “own” your decision, though of course you may be informed by social science data, recommendations of others, and so on. A second possibility is that such impersonal decision-making processes are not seen as authentic, where authentic decision making is one in which you intentionally and knowledgably choose an option in a way that is “true to yourself.” Such decision making can be particularly important in contexts where one is making a life-changing decision of great import, such as the choice to emigrate, start a family, or embark on a major career change.

Sign in / Sign up

Export Citation Format

Share Document