Automated Author ProfileCavazza, Nicoletta
Cavazza, Nicoletta
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: 0.4 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The debate arisen around the weakening of the traditional cleavages’ heuristic power in explaining vote suggests considering the role of lifestyles in designing politically meaningful social aggregates. We investigated the relationship between lifestyle and voting behavior, establishing the degree to which this relationship traces the effect of the socio-structural categories (e.g. social class) or is, at least in part, independent from them. Through a k-means clustering, we individuated a typology of four Italian lifestyles; we showed its relation to socio-demographic features and its ability to discriminate participants’ political attitudes. The subscription to each lifestyle was significantly associated with voting behavior, net of the variance accounted for by the traditional cleavages. Theoretical implication and further direction of research are discussed.
Authors
- Cavazza, Nicoletta ;
- Corbetta Piergiorgio