scholarly journals The Comparative Legislators Database

2020 ◽  
Author(s):  
Sascha Göbel ◽  
Simon Munzert
Keyword(s):  
Visual Information ◽  
Comparative Research ◽  
R Package ◽  
Micro Data ◽  
Public Attention ◽  
Social Scientists ◽  
Individual Level ◽  
Open Collaboration ◽  
Ready Access ◽  
Collaboration Platforms

Knowledge about political representatives’ behavior is crucial for a deeper understanding of politics and policy-making processes. Yet resources on legislative elites are scattered, often specialized, limited in scope, or not always accessible. We introduce the Comparative Legislators Database (CLD), which joins micro-data collection efforts on open-collaboration platforms and other sources, and integrates with renowned political science datasets. The CLD includes political, sociodemographic, career, online presence, public attention, and visual information for over 45,000 contemporary and historical politicians from ten countries. We provide a straightforward and open-source interface to the database through an R package, offering targeted, fast, and analysis-ready access in formats familiar to social scientists and standardized across time and space. We verify the data against human-coded datasets and illustrate its use for investigating legislator prominence and turnover. The CLD contributes to a central hub for versatile information about legislators and their behavior, supporting individual-level comparative research over long periods.

scholarly journals The Comparative Legislators Database

2021 ◽  
pp. 1-11 ◽  
Author(s):  
Sascha Göbel ◽  
Simon Munzert
Keyword(s):  
Visual Information ◽  
Comparative Research ◽  
R Package ◽  
Micro Data ◽  
Public Attention ◽  
Social Scientists ◽  
Individual Level ◽  
Open Collaboration ◽  
Ready Access ◽  
Collaboration Platforms

Abstract Knowledge about political representatives' behavior is crucial for a deeper understanding of politics and policy-making processes. Yet resources on legislative elites are scattered, often specialized, limited in scope or not always accessible. This article introduces the Comparative Legislators Database (CLD), which joins micro-data collection efforts on open-collaboration platforms and other sources, and integrates with renowned political science datasets. The CLD includes political, sociodemographic, career, online presence, public attention, and visual information for over 45,000 contemporary and historical politicians from ten countries. The authors provide a straightforward and open-source interface to the database through an R package, offering targeted, fast and analysis-ready access in formats familiar to social scientists and standardized across time and space. The data is verified against human-coded datasets, and its use for investigating legislator prominence and turnover is illustrated. The CLD contributes to a central hub for versatile information about legislators and their behavior, supporting individual-level comparative research over long periods.

scholarly journals Simulation Studies as a Tool to Understand Bayes Factors

2021 ◽  
Vol 4 (1) ◽  
pp. 251524592097262
Author(s):  
Don van Ravenzwaaij ◽  
Alexander Etz
Keyword(s):  
Simulation Study ◽  
Prior Distribution ◽  
Bayes Factor ◽  
R Package ◽  
Bayes Factors ◽  
Simulation Studies ◽  
Social Scientists ◽  
Simple Simulation ◽  
Set Up

When social scientists wish to learn about an empirical phenomenon, they perform an experiment. When they wish to learn about a complex numerical phenomenon, they can perform a simulation study. The goal of this Tutorial is twofold. First, it introduces how to set up a simulation study using the relatively simple example of simulating from the prior. Second, it demonstrates how simulation can be used to learn about the Jeffreys-Zellner-Siow (JZS) Bayes factor, a currently popular implementation of the Bayes factor employed in the BayesFactor R package and freeware program JASP. Many technical expositions on Bayes factors exist, but these may be somewhat inaccessible to researchers who are not specialized in statistics. In a step-by-step approach, this Tutorial shows how a simple simulation script can be used to approximate the calculation of the Bayes factor. We explain how a researcher can write such a sampler to approximate Bayes factors in a few lines of code, what the logic is behind the Savage-Dickey method used to visualize Bayes factors, and what the practical differences are for different choices of the prior distribution used to calculate Bayes factors.

scholarly journals Meffil: efficient normalisation and analysis of very large DNA methylation samples

2017 ◽  
Author(s):  
Josine Min ◽  
Gibran Hemani ◽  
George Davey Smith ◽  
Caroline Relton ◽  
Matthew Suderman
Keyword(s):  
Dna Methylation ◽  
Association Studies ◽  
R Package ◽  
Individual Level ◽  
Technological Advances ◽  
Level Data ◽  
Fixed And Random Effects ◽  
R Packages ◽  
Meta Analyses ◽  
Dramatic Growth

AbstractBackgroundTechnological advances in high throughput DNA methylation microarrays have allowed dramatic growth of a new branch of epigenetic epidemiology. DNA methylation datasets are growing ever larger in terms of the number of samples profiled, the extent of genome coverage, and the number of studies being meta-analysed. Novel computational solutions are required to efficiently handle these data.MethodsWe have developed meffil, an R package designed to quality control, normalize and perform epigenome-wide association studies (EWAS) efficiently on large samples of Illumina Infinium HumanMethylation450 and MethylationEPIC BeadChip microarrays. We tested meffil by applying it to 6000 450k microarrays generated from blood collected for two different datasets, Accessible Resource for Integrative Epigenomic Studies (ARIES) and The Genetics of Overweight Young Adults (GOYA) study.ResultsA complete reimplementation of functional normalization minimizes computational memory requirements to 5% of that required by other R packages, without increasing running time. Incorporating fixed and random effects alongside functional normalization, and automated estimation of functional normalisation parameters reduces technical variation in DNA methylation levels, thus reducing false positive associations and improving power. We also demonstrate that the ability to normalize datasets distributed across physically different locations without sharing any biologically-based individual-level data may reduce heterogeneity in meta-analyses of epigenome-wide association studies. However, we show that when batch is perfectly confounded with cases and controls functional normalization is unable to prevent spurious associations.Conclusionsmeffil is available online (https://github.com/perishky/meffil/) along with tutorials covering typical use cases.

Sympathy and Social Order

2008 ◽  
Vol 71 (4) ◽  
pp. 379-397 ◽  
Author(s):  
Kyle Irwin ◽  
Tucker Mcgrimmon ◽  
Brent Simpson
Keyword(s):  
Social Order ◽  
Social Values ◽  
Empirical Work ◽  
Future Research ◽  
Social Scientists ◽  
Generalized Trust ◽  
Individual Level ◽  
Self Interest ◽  
Greater Good ◽  
Vignette Experiment

Social order is possible only if individuals forgo the narrow pursuit of self-interest for the greater good. For over a century, social scientists have argued that sympathy mitigates self-interest and recent empirical work supports this claim. Much less is known about why actors experience sympathy in the first place, particularly in fleeting interactions with strangers, where cooperation is especially uncertain. We argue that perceived interdependence increases sympathy towards strangers. Results from our first study, a vignette experiment, support this claim and suggests a situational solution to social dilemmas. Meanwhile, previous work points to two strong individual-level predictors of cooperation: generalized trust and social values. In Study Two we address the intersection of situational and individual-level explanations to ask: does situational sympathy mediate these individual-level predictors of cooperation? Results from the second study, a laboratory experiment, support our hypotheses that sympathy mediates the generalized trust-cooperation link and the relationship between social values and cooperation. The paper concludes with a discussion of limitations of the present work and directions for future research.

scholarly journals Job tasks and the comparative structure of income and employment: Routine task intensity and offshorability for the LIS*

2018 ◽  
Vol 59 (2) ◽  
pp. 81-109 ◽  
Author(s):  
Matthew C Mahutga ◽  
Michaela Curran ◽  
Anthony Roberts
Keyword(s):  
Work Hours ◽  
Social Scientists ◽  
Data Infrastructure ◽  
Individual Level ◽  
Job Tasks ◽  
The North ◽  
Income Polarization ◽  
Comparative Structure ◽  
Global North ◽  
Country Specific

Comparative sociologists have long considered occupations to be a key source of inequality. However, data constraints make comparative research on two of the more important contemporary drivers of occupational stratification – globalization and technological change – relatively scarce. This article introduces a new dataset on occupational ‘routine task intensity’ (RTI) and ‘offshorability’ (OFFS) for use with the Luxembourg Income Study (LIS). To produce these data, we recoded 23 country-specific occupational schemes (74 LIS country-years) to the two-digit ISCO-88 scheme. When combined with the handful of LIS countries already reporting their occupations in ISCO-88, we produce individual level RTI and OFFS scores for 38 LIS countries and 160 LIS country-years. To assess the validity of these recodes, we compare average labor-income ratios predicted by recoded ISCO-88 occupational categories to those predicted by reported ISCO-88 occupational categories within countries that transitioned from country-specific to ISCO-88 codes over time. To assess the utility of these RTI and OFFS scores and advance the literature on income polarization, we analyze their association with work hours and labor incomes in the global North and South. Both covariates correlate with work hours in ways that are consistent with previous research and additional theoretical considerations. Moreover, we show that both RTI and OFFS contribute to income polarization directly in the North, but not in the South. This article generates a public good data infrastructure that will be of use to a wide variety of social scientists, and brings new evidence to bear on the question of income polarization in rich democracies.

Why Do People Become Perpetrators of Genocide?

2019 ◽  
pp. 312-334
Author(s):  
Ying Tang ◽  
Leonard S. Newman
Keyword(s):  
Human Behavior ◽  
Contextual Factors ◽  
Psychological Explanation ◽  
Social Psychological ◽  
Social Scientists ◽  
Individual Level

Explanations of the behavior of genocide perpetrators—and evildoers in general—are not always well received. Social scientists condemn evil, but they also seek to understand and explain it. However, explanations of wrongdoing in terms of general principles of human behavior can strike many people as a way of making excuses for it. Research is reviewed indicating that explaining wrongdoing in terms of situational or contextual factors (i.e., a social psychological explanation) is especially likely to be perceived as an attempt to exonerate the wrongdoer. Research also reveals cultural and individual-level moderators of this tendency. Interactionist accounts trigger less resistance. Psychological accounts of genocide are meant not to absolve perpetrators of responsibility but to inform the prevention of future genocides.

scholarly journals How to do things with epigenetics: An investigation into the use of metaphors to promote alternative approaches to health and social science, and their implications for interdisciplinary collaboration

2019 ◽  
Vol 59 (1) ◽  
pp. 59-92 ◽  
Author(s):  
Brigitte Nerlich ◽  
Aleksandra Stelmach ◽  
Catherine Ennis
Keyword(s):  
Social Science ◽  
Interdisciplinary Collaboration ◽  
Social Representations ◽  
Well Being ◽  
Public Attention ◽  
Social Scientists ◽  
Alternative Health ◽  
The Public ◽  
Alternative Approaches ◽  
The Public Sphere

Epigenetics is a multifaceted field within genetics and genomics which focuses on discovering mechanisms involved in gene expression and regulation. It came to public attention around the turn of the millennium when the human genome began to be deciphered. Initial findings from epigenetics research held the promise of changing how we think about health and illness, evolution and heredity; speculations about how individuals and populations could begin to control such processes through epigenetics were then picked up in the public realm. In this article we concentrate on two normally distant domains within the public sphere: the advertising of alternative health products and services, and the promotion of alternative approaches to social science, especially around how social science deals with the ‘biosocial’. Using insights from social representations theory and methods aligned with metaphor analysis, we investigate the meanings of epigenetics rooted in the use of metaphors and commonplaces that are circulating in current popular parlance and that are used to promote academic theories and ideas as well as tangible products and services. We compare and contrast them and assess their implications for collaborations between natural and social scientists. Our findings reveal some surprising similarities between the metaphors and commonplaces used by advertisers and social scientists, based in large part on the fact that both groups draw on the work of prominent epigeneticists. In both instances some fundamental tenets of mainstream biology are contested, and hopes are created for improving individual or population well-being through the manipulation of epigenetic mechanisms. Both domains share some misunderstandings of epigenetics that might lead to problems with interdisciplinary collaborations between social and natural scientists.

scholarly journals Apples and Oranges? The Problem of Equivalence in Comparative Research

2011 ◽  
Vol 19 (4) ◽  
pp. 471-487 ◽  
Author(s):  
Daniel Stegmueller
Keyword(s):  
Item Response ◽  
Comparative Research ◽  
Large Scale ◽  
Structural Parameters ◽  
Simultaneous Estimation ◽  
Response Behavior ◽  
Item Response Model ◽  
Individual Level ◽  
Level Data ◽  
Cross National

Researchers in comparative research are increasingly relying on individual level data to test theories involving unobservable constructs like attitudes and preferences. Estimation is carried out using large-scale cross-national survey data providing responses from individuals living in widely varying contexts. This strategy rests on the assumption of equivalence, that is, no systematic distortion in response behavior of individuals from different countries exists. However, this assumption is frequently violated with rather grave consequences for comparability and interpretation. I present a multilevel mixture ordinal item response model with item bias effects that is able to establish equivalence. It corrects for systematic measurement error induced by unobserved country heterogeneity, and it allows for the simultaneous estimation of structural parameters of interest.

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