scholarly journals Alternatives to Social Science One

2020 ◽  
Vol 53 (4) ◽  
pp. 710-711
Author(s):  
Margaret Levi ◽  
Betsy Rajala
Keyword(s):  
Social Science ◽  
Administrative Data ◽  
Third Party ◽  
Social Scientists ◽  
Social Good ◽  
Individual Level ◽  
Level Data ◽  
Highly Sensitive ◽  
Research Facilities ◽  
Sensitive Individual

ABSTRACTThis article responds to King and Persily’s (2019) proposal for a new model of industry–academic partnership using an independent third party to mediate between firms and academics. We believe this is a reasonable proposal for highly sensitive individual-level data, but it may not be appropriate for all types of data. We explore alternative options to their proposal, including Administrative Data Research Facilities, Data Collaboratives at GovLab, and Tech Data for Social Good Initiative at the Center for Advanced Study in the Behavioral Sciences. We believe social scientists should continue to explore, evaluate, and scale a variety of industry–academic data-sharing models.

scholarly journals Introduction

2021 ◽  
pp. 1-9
Author(s):  
Guillaume Marois ◽  
Samir KC
Keyword(s):  
Social Sciences ◽  
Good Option ◽  
Population Projections ◽  
Social Scientists ◽  
Statistical Software ◽  
Individual Level ◽  
Random Experiment ◽  
Level Data ◽  
Microsimulation Models

AbstractThis chapter introduces the purpose of the book. When a researcher needs to perform microsimulation for population projections, building its own model with a common statistical software such as SAS might a good option, because this software is widely used among scholars and is taught in most social sciences departments. We define what is microsimulation: a modelling based on individual-level data rather than aggregated level data, in which transitions between the states are determined stochastically with a random experiment. We finally provide some examples of microsimulation models used by social scientists.

scholarly journals Towards victim-oriented crime modelling in a social science e-infrastructure

2011 ◽  
Vol 369 (1949) ◽  
pp. 3353-3371 ◽  
Author(s):  
Nick Malleson ◽  
Mark Birkin
Keyword(s):  
Social Science ◽  
Social Research ◽  
Research Programme ◽  
Prevention Strategies ◽  
Social Scientists ◽  
Agent Based ◽  
Individual Level ◽  
Realistic Representation ◽  
The Uk ◽  
Burglary Risk

The National e-Infrastructure for Social Simulation (NeISS) is a multi-disciplinary collaboration between computation and social science within the UK Digital Social Research programme. The project aims to develop new tools and services for social scientists and planners to assist in performing ‘what-if’ scenario predictions in a variety of policy contexts. A key part of the NeISS remit is to explore real-world scenarios and evaluate real policy applications. Research into the processes and drivers behind crime is an important application area that has major implications for both improving crime-related policy and developing effective crime prevention strategies. This paper will discuss how the current e-infrastructure and available microsimulation tools can be used to improve an existing agent-based burglary simulation (BurgdSIM) by including a more realistic representation of the victims of crime. Results show that the model produces different spatial patterns when individual-level victim data are used and a risk profile of the synthetic victims suggests which types of people have the largest burglary risk.

Research Facilities in Turkey

1975 ◽  
Vol 9 (2) ◽  
pp. 20-29
Author(s):  
Frank Tachau
Keyword(s):  
Social Sciences ◽  
Social Science ◽  
Political Change ◽  
Social Economic ◽  
Social Science Research ◽  
Science Research ◽  
Social Scientists ◽  
The Social ◽  
Trained Personnel ◽  
Research Facilities

In a report on the climate for social science research in Turkey published some seven years ago, Edwin J. Cohn noted that there had been a considerable intensification of interest and activity in the social sciences in Turkey, spurred both by the training of Turkish social scientists and by the increased interest of European and American scholars in Turkish experience with rapid social, economic, and political change. At the same time, Cohn reported, “the climate for research, especially research by Americans, has deteriorated…” This assessment remains basically accurate. Of course, in the intervening years, there have been further developments. Two in particular will be dealt with here: continued increase in institutions, facilities, and trained personnel on the Turkish side; and greater formalization of official rules governing the conduct of research by foreigners.

scholarly journals ADRF Network Hosts Research Conference to Advance Uses of Administrative Data in the United States

2018 ◽  
Vol 3 (1) ◽  
Author(s):  
Monica M King
Keyword(s):  
United States ◽  
Social Science ◽  
Administrative Data ◽  
Social Science Research ◽  
Science Research ◽  
The United States ◽  
Massive Data ◽  
Building Trust ◽  
Research Facilities ◽  
Sector Data

The Administrative Data Research Facilities (ADRF) Network is a new U.S.-based effort aimed at advancing the uses of administrative data in social science research. Together with Georgetown University’s Massive Data Institute, the ADRF Network hosted its first conference in November 2017 to share approaches and build collaborative opportunities. The conference illustrated the importance of private sector data, the need for data intermediaries, and the essential process of building trust in moving forward this emerging field in the United States. 

Coleman’s Boat Revisited: Causal Sequences and the Micro-macro Link

2018 ◽  
Vol 36 (4) ◽  
pp. 368-391 ◽  
Author(s):  
Gustav Ramström
Keyword(s):  
Social Science ◽  
Macro Level ◽  
Social Scientists ◽  
Individual Level ◽  
Macro Model ◽  
Empirical Social Science ◽  
The Individual

This article argues that empirical social scientists can be freed from having to account for “micro-to-macro transitions.” The article shows, in opposition to the (still) dominant perspective based on Coleman’s macro-micro-macro model, that no micro-macro transitions or mechanisms connect the individual level to the macro level in empirical social science. Rather, when considering that social macro entities and properties are micro manifest rather than macro manifest, it becomes clear that the micro-macro move in empirical social science is purely conceptual or analytical.

Linking Individual-level Facebook Posts with Psychological and Health Data in an Epidemiologic Cohort: A Feasibility Study (Preprint)

2021 ◽  
Author(s):  
Peter James ◽  
Claudia Trudel-Fitzgerald ◽  
Harold H Lee ◽  
Hayami K Koga ◽  
Laura D Kubzansky ◽  
...  
Keyword(s):  
Social Media ◽  
Older Women ◽  
Psychological Factors ◽  
Data Privacy ◽  
Third Party ◽  
Health Study ◽  
Participation Rates ◽  
Individual Level ◽  
Exit Survey ◽  
Level Data

BACKGROUND Psychological factors (e.g., depression, optimism) and related biological and behavioral responses are associated with numerous physical health outcomes. The majority of research in this area relies on self-reported assessments of psychological factors, which are difficult to scale because they may be expensive to administer and time-consuming to complete. Investigators are increasingly interested in using social media as a novel and convenient platform for obtaining information rapidly in large populations. OBJECTIVE We evaluated the feasibility of obtaining Facebook data from a large ongoing cohort of midlife and older women which may be used to assess psychological functioning efficiently with low cost. METHODS This protocol was conducted with participants in the Nurses’ Health Study II (NHSII) which was started in 1989 with biennial follow-ups. Facebook does not share data readily; therefore, we developed procedures to enable women to download and transfer their Facebook data to the cohort servers (for linkage with other study data they have provided). Since privacy is a critical concern when collecting individual-level data, we partnered with a third-party software developer, Digi.me, to enable participants to obtain their own Facebook data and to send it securely to our research team. In 2020, we invited a subset of the 18,519 NHSII participants (aged 56-73 years) via email to participate. Women were selected if they reported on the 2017-2018 questionnaire that they regularly posted to Facebook and were still active cohort participants. We included an exit survey for those who chose not to participate to gauge reasons for non-participation. RESULTS We invited 309 women to participate. Few women signed the consent form (N=52) and only three used the Digi.me app to download and transfer their Facebook data. These low participation rates were observed despite modifying our protocol between waves of recruitment, including by 1) excluding active healthcare workers, who might be less available to participate due to the pandemic; 2) developing a Frequently Asked Questions factsheet to provide more information regarding the protocol; and 3) simplifying the instructions for using the Digi.me app. On our exit survey, reasons most commonly reported for not participating were concerns regarding data privacy and hesitation sharing personal Facebook posts. The low participation rates suggest that obtaining individual-level Facebook data in a cohort of middle-aged and older women may be challenging. CONCLUSIONS In this cohort of midlife and older women who were actively participating for over three decades, we were largely unable to obtain permission to access to individual-level data from participants’ Facebook accounts. Despite working with a third-party to customize an app to implement safeguards for privacy, data privacy remained a key concern in these women. Future studies aiming to leverage individual-level social media should explore alternate populations or means of sharing social media data.

scholarly journals Behavior under Extreme Conditions: The Titanic Disaster

2011 ◽  
Vol 25 (1) ◽  
pp. 209-222 ◽  
Author(s):  
Bruno S Frey ◽  
David A Savage ◽  
Benno Torgler
Keyword(s):  
Extreme Conditions ◽  
Social Scientists ◽  
Physical Strength ◽  
Individual Level ◽  
Life And Death ◽  
Probability Of Survival ◽  
The People ◽  
Level Data ◽  
Children First ◽  
Other Regarding

During the night of April 14, 1912, the RMS Titanic collided with an iceberg on her maiden voyage. Two hours and 40 minutes later she sank, resulting in the loss of 1,501 lives—more than two-thirds of her 2,207 passengers and crew. This remains one of the deadliest peacetime maritime disasters in history and by far the most famous. For social scientists, evidence about how people behaved as the Titanic sunk offers a quasi-natural field experiment to explore behavior under extreme conditions of life and death. A common assumption is that in such situations, self-interested reactions will predominate and social cohesion is expected to disappear. However, empirical evidence on the extent to which people in the throes of a disaster react with self-regarding or with other-regarding behavior is scanty. The sinking of the Titanic posed a life-or-death situation for its passengers. The Titanic carried only 20 lifeboats, which could accommodate about half the people aboard, and deck officers exacerbated the shortage by launching lifeboats that were partially empty. Failure to secure a seat in a lifeboat virtually guaranteed death. We have collected individual-level data on the passengers and crew on the Titanic, which allow us to analyze some specific questions: Did physical strength (being male and in prime age) or social status (being a first- or second-class passenger) raise the survival chance? Was it favorable for survival to travel alone or in company? Does one's role or function (being a crew member or a passenger) affect the probability of survival? Do social norms, such as “Women and children first!” have any effect? Does nationality affect the chance of survival? We also explore whether the time from impact to sinking might matter by comparing the sinking of the Titanic over nearly three hours to the sinking of the Lusitania in 1915, which took only 18 minutes from when the torpedo hit the ship.

scholarly journals Using Electromagnetic Signal Propagation Models for Radio and Television Broadcasts: An Introduction

2018 ◽  
Vol 26 (3) ◽  
pp. 348-355 ◽  
Author(s):  
Charles Crabtree ◽  
Holger L. Kern
Keyword(s):  
Media Exposure ◽  
Signal Strength ◽  
Signal Propagation ◽  
Electromagnetic Signal ◽  
Social Scientists ◽  
Propagation Models ◽  
Radio Stations ◽  
Individual Level ◽  
Level Data ◽  
Television Signal

This note offers an introduction to electromagnetic signal propagation models, which can be used to model terrestrial radio and television signal strength across space. Such data are useful to social scientists interested in identifying the effects of mass media broadcasts when (i) individual-level data on media exposure do not exist or when (ii) media exposure, while observed, is not exogenous. We illustrate the use of electromagnetic signal propagation models by creating a signal strength measure of military-controlled radio stations during the 2012 coup in Mali.

scholarly journals Privacy protected graphical functionality in DataSHIELD

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Demetris Avraam ◽  
Amadou Gaye ◽  
Julia Isaeva ◽  
Thomas Burton ◽  
Rebecca Wilson ◽  
...  
Keyword(s):  
Data Privacy ◽  
Epidemiological Studies ◽  
Statistical Properties ◽  
Sensitive Information ◽  
Single Individual ◽  
Individual Level ◽  
Novel Approach ◽  
Level Data ◽  
Graphical Illustration ◽  
Sensitive Individual

ABSTRACT ObjectivesIn several disciplines such as in biomedicine and social sciences the analysis of individual-level data or the co-analysis of data from different studies requires the pooling and the sharing of those data. However, sharing and combining sensitive individual-level data is often prohibited by ethico-legal constraints and other barriers such as the control maintenance and the huge sample sizes. The graphical illustration of microdata is also often forbidden as can potentially be unsecured on the identification of sensitive information. For example the plot of a standard scatterplot is disclosive as can explicitly specify the exact values of two measurements for each single individual. ApproachDataSHIELD (www.datashield.ac.uk) is a novel approach that allows the analysis of sensitive individual-level data and the co-analysis of such data from several studies simultaneously without physically pooling the data. ResultsDataSHIELD functionality consists of several functions that provide the flexibility of performing data analysis through different statistical techniques. A part of this environment includes a number of graphical-related functions for the graphical illustration of the statistical properties and relationships between different variables. We overview the graphical functions in DataSHIELD (ds.histogram, ds.heatmapPlot, ds.contourPlot) and demonstrate a number of new functions including ds.scatterPlot and ds.boxPlot developed based on the application of different computational approaches like the k-Nearest Neighbours algorithm and ensuring privacy protected analysis. ConclusionDataSHIELD graphical functionality has certain methodological features for the representation of the relationships between different variables preserving their statistical properties and assuring the data privacy protection. These graphical approaches can be used or enhanced for application in various areas where confidentiality and information sensitivity is considered, for example in longitudinal data and survival analysis, in epidemiological studies, in geospatial analysis and several others.

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