Counterfactual Analysis

2021 ◽  
pp. 64-67
Author(s):  
Shunsuke Sato
Keyword(s):  
Political Science ◽  
Necessary Conditions ◽  
Causal Analysis ◽  
Counterfactual Analysis ◽  
Social Scientists ◽  
Science History ◽  
Major Topic ◽  
Theoretical Statement ◽  
Research Designs ◽  
Small N

This chapter discusses counterfactual analysis. Counterfactual inference has been a major topic in methodological discussions in many disciplines such as political science, history, psychology, philosophy, and others. When social scientists attempt to assess hypotheses about the causes of phenomena, counterfactual propositions generally play an important role. Particularly in qualitative small-N research designs, counterfactuals are indispensable tools for causal analysis because all causal statements imply some kind of counterfactual. The theoretical statement ‘X causes Y’ implies that if X’s value were different, outcome Y would be different. Essentially, when scholars explain why a particular outcome Y occurred, they need to explain why Y happened, rather than other possible outcomes. When scholars make a proposition that includes necessary conditions, they clarify counterfactual implications: a logical format of necessary conditions — ‘if not X, then not Y’ — directly expresses a counterfactual’s consequent. Therefore, most social scientists inevitably use counterfactual analysis for various purposes. The chapter then looks at the criteria for evaluating counterfactual analysis.

Reflections on Local Population Studies and Social Science History

2018 ◽  
pp. 43-51
Author(s):  
Osamu Saito
Keyword(s):  
Social Science ◽  
Population Studies ◽  
Local Population ◽  
Local Source ◽  
Personal Reflection ◽  
Social Scientists ◽  
Science History ◽  
Social Science History ◽  
The Relationship ◽  
Source Materials

This personal reflection of more than 40 years' work on the supply of labour in a household context discusses the relationship between social science history (the application to historical phenomena of the tools developed by social scientists) and local population studies. The paper concludes that historians working on local source materials can give something new back to social scientists and social science historians, urging them to remake their tools.

Twin Studies and Politics

2019 ◽  
Author(s):  
Levente Littvay
Keyword(s):  
Political Science ◽  
Behavioral Genetics ◽  
Twin Studies ◽  
Social Scientists ◽  
Cross Sectional ◽  
Genetic Transmission ◽  
The Social ◽  
Direction Of Causation ◽  
Social Part ◽  
The Impact

As recently as 2005, John Alford and colleagues surprised political science with their twin study that found empirical evidence of the genetic transmission of political attitudes and behaviors. Reactions in the field were mixed, but one thing is for sure: it is not time to mourn the social part of the social sciences. Genetics is not the deterministic mechanism that social scientists often assume it to be. No specific part of DNA is responsible for anything but minute, indirect effects on political orientations. Genes express themselves differently in different contexts, suggesting that the political phenomenon behavioral political scientists take for granted may be quite volatile; hence, the impact of genetics is also much less stable in its foundations than initially assumed. Twin studies can offer a unique and powerful avenue to study these behavioral processes as they are more powerful than cross-sectional (or even longitudinal) studies not only for understanding heritability but also for asserting the direction of causation, the social (and, of course, genetic) pathways that explain how political phenomena are related to each other. This chapter aims to take the reader through this journey that political science has gone through over the past decade and a half and point to the synergies behavioral political science and behavioral genetics offer to the advancement of the discipline.

Genes, cognition, and social behavior: Next steps for foundations and researchers

2011 ◽  
Vol 30 (2) ◽  
pp. 65-87 ◽  
Author(s):  
Arthur Lupia
Keyword(s):  
Social Behavior ◽  
Political Science ◽  
National Science Foundation ◽  
Scientific Practices ◽  
Social Scientists ◽  
Research Areas ◽  
Unpublished Report ◽  
Summary Statement ◽  
The One ◽  
Scientific Value

Editor's note This well circulated but heretofore unpublished report is the summary statement of an interdisciplinary meeting of scholars convened by the National Science Foundation in Arlington, Virginia on June 28, 2010. The workshop, which was funded by the NSF's Political Science Program (Social, Behavioral & Economic Sciences Grant #1037831), was convened to answer two compelling questions: Are studies of social behavior that build from discoveries about genes and/or cognition of greater social and scientific value than studies of the same topics that ignore such factors? And, how can fundable research on genes, cognition, and politics generate transformative scientific practices, infrastructure, and findings of high social value? Assembled for the workshop were a group of scholars representing diverse yet increasingly connected research areas, including genetics, cognitive science and neuroscience, decision making and risk analysis, economics, political science, and sociology. The resulting report outlines the substantial challenges facing interdisciplinary research but also describes the considerable contributions to knowledge that could result from sustained collaborations between biologists, geneticists, and brain scientists on the one hand and social scientists on the other. Following this main report are three white papers by Jeremy Freese. Elizabeth Hammock, and Rose McDermott, which address importmant considerations related to the discussion. For a download of the full report, see http://www.isr.umich.edu.cps/workshop.Welcome.html.

scholarly journals Causal Interaction and Effect Modification: Same Model, Different Concepts

2017 ◽  
Author(s):  
Luke Keele ◽  
Randolph T. Stevenson
Keyword(s):  
Political Science ◽  
Regression Models ◽  
Interaction Analysis ◽  
Effect Modification ◽  
The Political ◽  
Science Literature ◽  
Causal Interaction ◽  
Single Treatment ◽  
Social Scientists ◽  
The Difference

Social scientists use the concept of interactions to study effect dependency. Such analyses can be conducted using standard regression models. However, an interaction analysis may represent either a causal interaction or effect modification. Under causal interaction, the analyst is interested in whether two treatments have differing effects when both are administered. Under effect modification, the analysts investigates whether the effect of a single treatment varies across levels of a baseline covariate. Importantly, the identification assumptions for these two types of analysis are very different. In this paper, we clarify the difference between these two types of interaction analysis. We demonstrate that this distinction is mostly ignored in the political science literature. We conclude with a review of several applications.

University of East Africa Social Science Conference

1966 ◽  
Vol 4 (4) ◽  
pp. 538-540
Author(s):  
Martin Lowenkopf
Keyword(s):  
Social Science ◽  
Political Science ◽  
East Africa ◽  
Sierra Leone ◽  
Rural Settlement ◽  
Social Scientists ◽  
Science Conference ◽  
The University ◽  
Political Decisions ◽  
Economic Criteria

This conference brought together over 70 social scientists from the Kenyan, Tanzanian, and Ugandan constituent Colleges of the University of East Africa (with visitors from Zambia, Ethiopia, Sierra Leone, and Rhodesia) for their annual inter-disciplinary, or rather trans-disciplinary, deliberations. Why ‘trans-disciplinary’? Because the historians discussed nationalism, politics, and church movements; political scientists discoursed on economics, rural settlement, agriculture, and education; sociologists criticised political decisions and economic criteria which hampered their investigations into resettlement programmes; and the economists, while speaking mostly about economics, were represented at virtually all panels, apparently to guard their disciplinary preserve against intrusions, presumptions and, in one case, elision with political science.

Global Bourdieu

2015 ◽  
Vol 14 (4) ◽  
pp. 565-586
Author(s):  
Niilo Kauppi ◽  
David Swartz
Keyword(s):  
International Relations ◽  
Political Science ◽  
Public Intellectual ◽  
Social Mechanisms ◽  
Social Scientists ◽  
Global Circulation ◽  
Multiple Factors ◽  
The Social ◽  
Social Domination ◽  
The Web

Pierre Bourdieu was a prolific scholar whose multifaceted work inspired research in a wide variety of areas. Beyond sociology we find his influence in anthropology, history, cultural studies, political science, and international relations. Particularly after 1995, when he engaged in a fight against neo-liberalism, he became the pre-eminent public intellectual. Bourdieu clearly stands in the pantheon of the greatest contemporary social scientists. This article explores the social mechanisms that enabled the global circulation of Bourdieu’s oeuvre. Multiple factors in multiple intellectual fields contributed to this process. There are “global Bourdieus.” Throughout his career Bourdieu was a defender of the dominated, and a sharp critic of established powers; his work provides individuals in a variety of central and peripheral fields weapons against social domination whatever its form. This narrative weds together his biography and oeuvre, and forms the web that unites him with the social carriers of his work globally.

Testing Causal Theories with Learned Proxies

2022 ◽  
Vol 25 (1) ◽  
Author(s):  
Dean Knox ◽  
Christopher Lucas ◽  
Wendy K. Tam Cho
Keyword(s):  
Political Science ◽  
Best Practice ◽  
Computational Models ◽  
Annual Review ◽  
Publication Date ◽  
Social Scientists ◽  
Theoretical Concepts ◽  
Point Estimates ◽  
Causal Diagrams ◽  
Causal Theories

Social scientists commonly use computational models to estimate proxies of unobserved concepts, then incorporate these proxies into subsequent tests of their theories. The consequences of this practice, which occurs in over two-thirds of recent computational work in political science, are underappreciated. Imperfect proxies can reflect noise and contamination from other concepts, producing biased point estimates and standard errors. We demonstrate how analysts can use causal diagrams to articulate theoretical concepts and their relationships to estimated proxies, then apply straightforward rules to assess which conclusions are rigorously supportable. We formalize and extend common heuristics for “signing the bias”—a technique for reasoning about unobserved confounding—to scenarios with imperfect proxies. Using these tools, we demonstrate how, in often-encountered research settings, proxy-based analyses allow for valid tests for the existence and direction of theorized effects. We conclude with best-practice recommendations for the rapidly growing literature using learned proxies to test causal theories. Expected final online publication date for the Annual Review of Political Science, Volume 25 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Women's Studies Programs

PMLA ◽  
1980 ◽  
Vol 95 (4) ◽  
pp. 670-675
Keyword(s):  
Political Science ◽  
Women's Studies ◽  
Educational Service ◽  
Science History ◽  
Women’S Studies ◽  
Maryland College ◽  
College Park ◽  
Interdisciplinary Courses

Most of the programs listed below are interdisciplinary; that is, they combine courses in literature, language, or culture with work in sociology, anthropology, economics, political science, history, philosophy, psychology, biology, and related fields. Many offer interdisciplinary courses as well as internships. Some programs offer minors or certificates; others offer major concentrations in women's studies or award A.A., B.A., M.A., or Ph.D. degrees. Where no coordinator, director, or chairperson is listed, the program may be in the process of organization, or it may have chosen to function through a committee or to rotate the administrative function.This list is maintained and published as an educational service of the National Women's Studies Association (Univ. of Maryland, College Park 20742) and of the Women's Studies Newsletter (Box 334, Old Westbury, NY 11568). Compilers for 1980 were Sharon Hagan and Elaine Reuben for NWSA, Shirley Frank and Florence Howe for the Women's Studies Newsletter.For additional copies of this list, send a stamped, self-addressed envelope to NWSA or to the Women's Studies Newsletter. Address additions or corrections for future lists to NWSA.

Institutional Logics and the Limits of Social Science Knowledge

2020 ◽  
Vol 60 (2) ◽  
pp. 203-213
Author(s):  
Jessica Blatt
Keyword(s):  
Social Science ◽  
Political Science ◽  
Institutional Logics ◽  
Science History ◽  
Social Science Knowledge ◽  
Race And Gender ◽  
Social Science History ◽  
Disciplinary History ◽  
History Of ◽  
And Gender

As someone whose training is in political science and who writes about the history of my own discipline, I admit to some hesitation in recommending future avenues of research for historians of education. For that reason, the following thoughts are directed toward disciplinary history broadly and social science history specifically. Moreover, the three articles that contributors to this forum were asked to use as inspiration suggest that any future I would recommend has been under way in one form or another for a while. For those reasons, I want to reframe my contribution as a reflection on a particular mode of analysis all three authors employed and how it may be particularly useful for exploring the questions of power, exclusion, and race- and gender-making in the academy that are present in all three articles and that explicitly animate two of them.

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