Automated Author ProfileLachat, Romain
Department of Political and Social Sciences, Universitat Pompeu Fabra
Lachat, Romain
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: 0.1 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Party identification and issue preferences are central explanatory factors in many voting choice models. Their effects on party preferences are usually understood to be additive. That is, issue preferences’ impact on party utilities is assumed to be the same among both party identifiers and nonidentifiers. This paper suggests an alternative model in which party identification moderates the impact of issues on the vote. The impact of issue preferences on party utilities should be weaker among voters who identify with a party. This hypothesis is tested using data from four recent Dutch election studies. The results show that identifying with a party substantially weakens the issue preference effect on party evaluations, particularly for the party with which a voter identifies.
Authors
- Lachat, Romain