Automated Author ProfileBarney, David
Burning Glass Technologies
Barney, David
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.3 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Past research has shown that issues vary significantly in their salience across citizens, explaining key outcomes in political behavior. Yet it remains unclear how individual-level differences in issue salience affect the measurement of latent constructs in public opinion, namely political ideology. In this paper, we test whether scaling approaches that fail to incorporate individual-level differences in issue salience could understate the predictive power of ideology in public opinion research. To systematically examine this assertion, we employ a series of latent variable models which incorporate both issue importance and issue position. We compare the results of these different and diverse scaling approaches to two survey datasets, investigating the implications of accounting for issue salience in constructing latent measures of ideology. Ultimately, we find that accounting for issue importance adds little information to a more basic approach that uses only issue positions, suggesting ideological signals for measurement models reside most prominently in the issue positions of individuals rather than the importance of those issues to the individual.
Authors
- Rice, Douglas ;
- Schaffner, Brian ;
- Barney, David