Justin H Gross
Biographic Data
| ID | 8744710 |
|---|---|
| NAME | Justin H Gross |
| GIVEN NAMES | Justin H |
| FAMILY NAME | Gross |
| SIGNATURE | GROSS J H |
| AFFILIATIONS | University of North Carolina at Chapel Hill |
| VERIFIED | No |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 98 |
| AUTHOR COUNT | 7 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2013 |
| LATEST PUBLICATION YEAR | 2019 |
| H-INDEX | 4 |
The Elusive Likely Voter
Political commentators have offered evidence that the “polling misses” of 2016 were caused by a number of factors. This project focuses on one explanation: that likely-voter models—tools used by preelection pollsters to predict which survey respondents are most likely to make up the electorate and, thus, whose responses should be used to calculate election predictions—were flawed. While models employed by different pollsters vary widely, it is di…
Rivals or Allies? A Multilevel Analysis of Cosponsorship within State Delegations in the U.S. Senate
The coordinated behavior of members of a state delegation to the U.S. Senate can provide constituents in a state greater representation in Congress. Despite this potentially improved level of representation through coordination, popular and scholarly accounts of the U.S. Senate often feature senators from the same state at odds with one another on a variety of policy issues. In this research, we investigate competing expectations regarding the fr…
Relational Concepts, Measurement, and Data Collection
Political phenomena are inherently relational, so it is natural that network analysis should come to play an important role in the study of politics. And yet relational data present special practical and methodological problems. The network data scholars would like to collect are often incomplete or altogether inaccessible. It is tempting to take whatever data are available and treat these as a proxy for the desired variables. This chapter review…
Twitter Taunts and Tirades: Negative Campaigning in the Age of Trump
What drives candidates to “go negative” and against which opponents? Using a unique dataset consisting of all inter-candidate tweets by the 17 Republican presidential candidates in the 2016 primaries, we assess predictors of negative affect online. Twitter is a free platform, and candidates therefore face no resource limitations when using it; this makes Twitter a wellspring of information about campaign messaging, given a level playing-field. Mo…
Testing What Matters (If You Must Test at All): A Context‐Driven Approach to Substantive and Statistical Significance
For over a half century, various fields in the behavioral and social sciences have debated the appropriateness of null hypothesis significance testing (NHST) in the presentation and assessment of research results. A long list of criticisms has fueled the so‐called significance testing controversy. The conventional NHST framework encourages researchers to devote excessive attention to statistical significance while underemphasizing practical (e.g.…
Measurement and theory in legislative networks: The evolving topology of Congressional collaboration
Keeping Your Friends Close and Your Enemies Closer? Information Networks in Legislative Politics
The authors contribute to the existing literature on the determinants of legislative voting by offering a social network-based theory about the ways that legislators’ social relationships affect floor voting behaviour. It is argued that legislators establish contacts with both political friends and enemies, and that they use the information they receive from these contacts to increase their confidence in their own policy positions. Social contact…
Keeping Your Friends Close and Your Enemies Closer? Information Networks in Legislative Politics
The authors contribute to the existing literature on the determinants of legislative voting by offering a social network-based theory about the ways that legislators’ social relationships affect floor voting behaviour. It is argued that legislators establish contacts with both political friends and enemies, and that they use the information they receive from these contacts to increase their confidence in their own policy positions. Social contact…
Testing What Matters (If You Must Test at All): A Context‐Driven Approach to Substantive and Statistical Significance
For over a half century, various fields in the behavioral and social sciences have debated the appropriateness of null hypothesis significance testing (NHST) in the presentation and assessment of research results. A long list of criticisms has fueled the so‐called significance testing controversy. The conventional NHST framework encourages researchers to devote excessive attention to statistical significance while underemphasizing practical (e.g.…
Twitter Taunts and Tirades: Negative Campaigning in the Age of Trump
What drives candidates to “go negative” and against which opponents? Using a unique dataset consisting of all inter-candidate tweets by the 17 Republican presidential candidates in the 2016 primaries, we assess predictors of negative affect online. Twitter is a free platform, and candidates therefore face no resource limitations when using it; this makes Twitter a wellspring of information about campaign messaging, given a level playing-field. Mo…
The Elusive Likely Voter
Political commentators have offered evidence that the “polling misses” of 2016 were caused by a number of factors. This project focuses on one explanation: that likely-voter models—tools used by preelection pollsters to predict which survey respondents are most likely to make up the electorate and, thus, whose responses should be used to calculate election predictions—were flawed. While models employed by different pollsters vary widely, it is di…
Rivals or Allies? A Multilevel Analysis of Cosponsorship within State Delegations in the U.S. Senate
The coordinated behavior of members of a state delegation to the U.S. Senate can provide constituents in a state greater representation in Congress. Despite this potentially improved level of representation through coordination, popular and scholarly accounts of the U.S. Senate often feature senators from the same state at odds with one another on a variety of policy issues. In this research, we investigate competing expectations regarding the fr…
Keeping Your Friends Close and Your Enemies Closer? Information Networks in Legislative Politics
The authors contribute to the existing literature on the determinants of legislative voting by offering a social network-based theory about the ways that legislators’ social relationships affect floor voting behaviour. It is argued that legislators establish contacts with both political friends and enemies, and that they use the information they receive from these contacts to increase their confidence in their own policy positions. Social contact…
Measurement and theory in legislative networks: The evolving topology of Congressional collaboration
Testing What Matters (If You Must Test at All): A Context‐Driven Approach to Substantive and Statistical Significance
For over a half century, various fields in the behavioral and social sciences have debated the appropriateness of null hypothesis significance testing (NHST) in the presentation and assessment of research results. A long list of criticisms has fueled the so‐called significance testing controversy. The conventional NHST framework encourages researchers to devote excessive attention to statistical significance while underemphasizing practical (e.g.…
Relational Concepts, Measurement, and Data Collection
Political phenomena are inherently relational, so it is natural that network analysis should come to play an important role in the study of politics. And yet relational data present special practical and methodological problems. The network data scholars would like to collect are often incomplete or altogether inaccessible. It is tempting to take whatever data are available and treat these as a proxy for the desired variables. This chapter review…
Twitter Taunts and Tirades: Negative Campaigning in the Age of Trump
What drives candidates to “go negative” and against which opponents? Using a unique dataset consisting of all inter-candidate tweets by the 17 Republican presidential candidates in the 2016 primaries, we assess predictors of negative affect online. Twitter is a free platform, and candidates therefore face no resource limitations when using it; this makes Twitter a wellspring of information about campaign messaging, given a level playing-field. Mo…
Rivals or Allies? A Multilevel Analysis of Cosponsorship within State Delegations in the U.S. Senate
The coordinated behavior of members of a state delegation to the U.S. Senate can provide constituents in a state greater representation in Congress. Despite this potentially improved level of representation through coordination, popular and scholarly accounts of the U.S. Senate often feature senators from the same state at odds with one another on a variety of policy issues. In this research, we investigate competing expectations regarding the fr…
The Elusive Likely Voter
Political commentators have offered evidence that the “polling misses” of 2016 were caused by a number of factors. This project focuses on one explanation: that likely-voter models—tools used by preelection pollsters to predict which survey respondents are most likely to make up the electorate and, thus, whose responses should be used to calculate election predictions—were flawed. While models employed by different pollsters vary widely, it is di…
Computer Science (7 works) · Political science (6 works) · Electoral Systems and Political Participation (5 works) · Politics (5 works) · Sociology (5 works) · Law (4 works) · Social Media and Politics (4 works) · Econometrics (3 works) · Economics (3 works) · Legislature (3 works)