Automated Author ProfileArico, Fabio
University of East Anglia
Arico, Fabio
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: 4.3 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
For Canada, the United Kingdom, and the United States, we illuminate the landscape for a relatively new and evolving role: full-time, teaching-track economists who work in the same departments as research-track economists, but with a greater emphasis on teaching.
We use in-depth interviews and a survey of teaching-track economists in the three countries and employ a mixed-methods approach.
A cohesive, cross-country, multi-institution comparison enables learning from a variety of contexts. Our findings inform decision-making processes, initiate conversations among multiple constituents, generate ideas, raise salient questions, and identify relative strengths and weaknesses of different teaching-track models.
The qualitative and quantitative raw data are IRB and GDPR protected and cannot be shared beyond the research team. In lieu of a replication package we share detailed description of the study design and research methodology, all code and the associated log-files.
Authors
- Spielmann, Christian ;
- Hoyt, Gail ;
- Murdock, Jennifer ;
- Jenkins, Cloda ;
- Elliott, Caroline ;
- Lait, Ashley ;
- Arico, Fabio ;
- Cohen, Avi ;
- Birdi, Alvin ;
- Emerson, Tisha
For Canada, the United Kingdom, and the United States, we illuminate the landscape for a relatively new and evolving role: full-time, teaching-track economists who work in the same departments as research-track economists, but with a greater emphasis on teaching.
We use in-depth interviews and a survey of teaching-track economists in the three countries and employ a mixed-methods approach.
A cohesive, cross-country, multi-institution comparison enables learning from a variety of contexts. Our findings inform decision-making processes, initiate conversations among multiple constituents, generate ideas, raise salient questions, and identify relative strengths and weaknesses of different teaching-track models.
The qualitative and quantitative raw data are IRB and GDPR protected and cannot be shared beyond the research team. In lieu of a replication package we share detailed description of the study design and research methodology, all code and the associated log-files.
Authors
- Spielmann, Christian ;
- Hoyt, Gail ;
- Murdock, Jennifer ;
- Jenkins, Cloda ;
- Elliott, Caroline ;
- Lait, Ashley ;
- Arico, Fabio ;
- Cohen, Avi ;
- Birdi, Alvin ;
- Emerson, Tisha