How to Lose Cases and Influence People
Datos Bibliográficos
| ID | 6170147 |
|---|---|
| Autores | Rachael K Hinkle (0000-0003-4324-0963, University at Buffalo, State University of New York, autor de correspondencia), Michael J Nelson (0000-0002-7665-7557, Pennsylvania State University) |
| Año | 2017 |
| Volumen | 8 |
| Número | 2 |
| Páginas | 195-221 |
| Fecha de publicación | 2017-12-20 |
| Peer Reviewed | Sí |
| Open Access | No |
| Tipo | ARTICLE |
| Revista | Statistics Politics and Policy (JOURNAL) |
| Identificadores de la revista | ISSN: 2151-7509 • E-ISSN: 2194-6299 |
| Editorial | De Gruyter (PUBLISHER • DE) |
| DOI | 10.1515/spp-2017-0013 |
| OpenAlex | W2797239231 |
| Idioma | EN |
| Citas recibidas | 3 |
| Referencias citadas | 16 |
Dissenting opinions are common in the US Supreme Court even though they take time and effort, risk infuriating colleagues, and have no precedential value. In spite of these drawbacks, dissents can potentially contribute to future legal development. We theorize that dissenting justices who use more memorable language are more successful in achieving such long-term impact. To test this theory, we amass an original dataset of citations to dissenting opinions extracted directly from majority opinion text. We further leverage these texts to build an algorithm that quantifies the distinctiveness of dissenting language within a dynamic context. Our results indicate that dissents using more negative emotion and more distinctive words are cited more in future majority opinions. These results contribute to our understanding of how language can influence long-term policy development
Context (archaeology · Dissenting opinion · Leverage (statistics · Optimal distinctiveness theory · Political science · Public relations · Supreme court · Computer Science · History · Judicial and Constitutional Studies · Law · Law in Society and Culture · Legal Education and Practice Innovations · Psychology · Social Psychology
Measuring Emotional Expression with the Linguistic Inquiry and Word Count
Emotional Stimuli, Divided Attention, and Memory
Influence of Emotion on Memory for Temporal Information
The Incumbent in the Living Room
Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953–1999
The Norm of Consensus on the U.S. Supreme Court
Legal Constraint in the US Courts of Appeals
Dissent in American Courts
Should I Use Fixed or Random Effects
Voters, Emotions, and Memory
Back to the Future
Framing Theory
| Obras citantes distintas | 3 |
|---|---|
| Citas por año | 0,5 |
| Intervalo de citas | 2020 - 2025 (6) |
| Velocidad de citación | recent |
| Altamente citado | No |
| Tipos de cita | Neutras: 3 |