Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if any of the following hold:
it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the
threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.
Countries citing papers authored by Robert Chambers
Since Specialization
Citations
This map shows the geographic impact of Robert Chambers'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 Robert Chambers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert Chambers more than expected).
This network shows the impact of papers produced by Robert Chambers. 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 Robert Chambers. The network helps show where Robert Chambers may publish in the future.
Robert Chambers is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics, Infectious Diseases, Organic Chemistry and Surgery, having authored 6 papers that have together received 1.2k indexed citations. Recurring topics across this work include Diverse Scientific and Engineering Research (1 paper) and Handwritten Text Recognition Techniques (1 paper). The work is most often cited by research in Business and International Management (68 citations), Development (87 citations), General Agricultural and Biological Sciences (167 citations), Safety Research (112 citations) and Urban Studies (78 citations). Robert Chambers has collaborated with scholars based in Japan. Their work appears in journals such as Journal of the ACM, Figshare, Practical Action Publishing eBooks and OpenDocs (Institute of Development Studies).
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.