Transparent Social Inquiry
Implications for Political Science
Bibliographic Data
| ID | 6232885 |
|---|---|
| Authors | Colin Elman (0000-0003-1004-4640, Syracuse University), Diana Kapiszewski (0000-0002-6408-2792, Georgetown University), Arthur Lupia (0000-0003-3220-1125, University of Michigan) |
| Year | 2018 |
| Volume | 21 |
| Issue | 1 |
| Pages | 29-47 |
| Publication date | 2018-05-11 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Annual Review of Political Science (BOOK_SERIES) |
| Journal identifiers | ISSN: 1094-2939 • E-ISSN: 1545-1577 |
| Publisher | Annual Reviews (PUBLISHER • US) |
| DOI | 10.1146/annurev-polisci-091515-025429 |
| OpenAlex | W2771109659 |
| Language | EN |
| Citations received | 33 |
| References cited | 34 |
Political scientists use diverse methods to study important topics. The findings they reach and conclusions they draw can have significant social implications and are sometimes controversial. As a result, audiences can be skeptical about the rigor and relevance of the knowledge claims that political scientists produce. For these reasons, being a political scientist means facing myriad questions about how we know what we claim to know. Transparency can help political scientists address these questions. An emerging literature and set of practices suggest that sharing more data and providing more information about our analytic and interpretive choices can help others understand the rigor and relevance of our claims. At the same time, increasing transparency can be costly and has been contentious. This review describes opportunities created by, and difficulties posed by, attempts to increase transparency. We conclude that, despite the challenges, consensus about the value and practice of transparency is emerging within and across political science's diverse and dynamic research communities
Engineering ethics · Epistemology · Political science · Politics · Public relations · Relevance (law · Rigour · Skepticism · Sociology · Transparency (behavior · Value (mathematics · Advanced Causal Inference Techniques · Computer Science · Law · Policy Transfer and Learning · Qualitative Comparative Analysis Research
Beyond the p < 0.05 trap
Mini-Public Replication
Open with care
Civically engaged research in political science
Welcome from the Editors
Big data meets open political science
Planning, implementing and reporting
Elite Interviewing in Political Science
Developing Interview Questions in Undergraduate Classrooms
Active Maintenance
Measuring actual discretion of the European Commission
The politics of urban regeneration in Liverpool and Everton FC’s alternate new stadium-project plans
Qualitative Research
Are Nonprobability Surveys Fit for Purpose
Challenges for Political Science Research Ethics in Autocracies
Why Do Voters Prefer Local Candidates? Evidence from a Danish Conjoint Survey Experiment
Shadowing as a Tool for Studying Political Elites
Crowdsourcing Reliable Local Data
Can We Do Better? Replication and Online Appendices in Political Science
Pre-Analysis Plans
Transparency for Text-Based Sources
Transparency in Practice in Qualitative Research
Reflections on Using Annotation for Transparent Inquiry in Mixed-Methods Research
Practical and Ethical Reasons for Pursuing a More Open Science
Qualitative Replication as a Pedagogical Approach to Teaching Research Methods
How Annotation for Transparent Inquiry Can Enhance Research Transparency in Qualitative Comparative Analysis
Improving Social Science
Empowering Transparency
Annotating Without Anxiety
Open Minds, Open Methods
Replicate Others as You Would Like to Be Replicated Yourself
A estrada dos tijolos amarelos
Qualitative Data Sharing
Promoting Transparency in Social Science Research
Publication bias in the social sciences
Badges to Acknowledge Open Practices
Promoting an open research culture
Interventions to Improve Research Participants' Understanding in Informed Consent for Research
Causal inference in statistics
Estimating causal effects of treatments in randomized and nonrandomized studies.
The Fair Guiding Principles for scientific data management and stewardship
The Oxford Handbook of the Science of Science Communication
Process Tracing
Antifragile
Legitimizing Political Science or Splitting the Discipline? Reflections on DA-RT and the Policy-making Role of a Professional Association
Explicit Bayesian Analysis for Process Tracing
Research Cycles
Can the Biomedical Research Cycle be a Model for Political Science
Trust, but Verify
Replication, Research Transparency, and Journal Publications
Transparency
Increasing the Credibility of Political Science Research
Data Access and Research Transparency in the Quantitative Tradition
Openness in Political Science
Data Access and Research Transparency in the Qualitative Tradition
Science Deserves Better
The American Political Science Association
Mixing Methods
The Logic of Process Tracing Tests in the Social Sciences
Publication Bias in Empirical Sociological Research
| Unique citing works | 33 |
|---|---|
| Citations per year | 4,71 |
| Citation span | 2019 - 2026 (8) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 33 |