Giulia Cavaliere

520 citations
19 papers · 223 indexed · h-index 9

Giulia Cavaliere

17 papers receiving 206 citations

Peers

Giulia Cavaliere
Comparison fields: 5 of 57
  • Reproductive Medicine 81
  • Business and International Management 15
  • Transplantation 11
  • Cognitive Neuroscience 67
  • Physiology 65
Replace César Palacios‐González with:
César Palacios‐González United Kingdom
Tina Rulli United States
Marcy Darnovsky United States
Bernard Baertschi Switzerland
Stephen Harbottle United Kingdom
Ramya Potabattula Germany
B.C. van Beers Netherlands
Katie M. Saulnier Canada
Marja Hietala Finland
Hilary Bok United States
Giulia Cavaliere relative to César Palacios‐González United Kingdom César Palacios‐González's profile →
Citations per field
00.5×1.5×2.2×
César Palacios‐González · 1×
Citations per year

Countries citing papers authored by Giulia Cavaliere

Since Specialization
Citations

This map shows the geographic impact of Giulia Cavaliere's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Giulia Cavaliere with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Giulia Cavaliere more than expected).

Fields of papers citing papers by Giulia Cavaliere

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Giulia Cavaliere. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Giulia Cavaliere. The network helps show where Giulia Cavaliere may publish in the future.

Co-authorship network

The 7 scholars most cited alongside Giulia Cavaliere, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Giulia Cavaliere Line = papers co-authored together Giulia Cavaliere links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 20250
2 20236
3 20231
4 20230
5 20221
6 20218
7 20205
8 20201
9 20198
10 201927
11 201825
12 201814
13 20183
14 20183
15 201812
16 201737
17 201755
18 20161
19 201616

About Giulia Cavaliere

Giulia Cavaliere is a scholar working on Reproductive Medicine, Cognitive Neuroscience, Gender Studies, Demography and Physiology, having authored 19 papers that have together received 223 indexed citations. Recurring topics across this work include Reproductive Health and Technologies (11 papers), Neuroethics, Human Enhancement, Biomedical Innovations (7 papers), Biomedical Ethics and Regulation (5 papers), CRISPR and Genetic Engineering (3 papers), Demographic Trends and Gender Preferences (3 papers), Ethics in medical practice (2 papers), Family Dynamics and Relationships (2 papers) and Assisted Reproductive Technology and Twin Pregnancy (2 papers). The work is most often cited by research in Reproductive Medicine (81 citations), Business and International Management (15 citations), Transplantation (11 citations), Cognitive Neuroscience (67 citations) and Physiology (65 citations). Giulia Cavaliere has collaborated with scholars based in United Kingdom, United States and Italy. Frequent co-authors include César Palacios‐González, Silvia Camporesi, Katrien Devolder, Alberto Giubilini, James Rupert Fletcher, Lorenzo Del Savio and Matteo Mameli. Their work appears in journals such as Journal of Medical Ethics, Medicine Health Care and Philosophy, Reproductive BioMedicine Online, BMC Medical Ethics and Bioethics.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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