Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Does Household Income Affect children’s Outcomes? A Systematic Review of the Evidence
This map shows the geographic impact of Kerris Cooper'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 Kerris Cooper with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kerris Cooper more than expected).
This network shows the impact of papers produced by Kerris Cooper. 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 Kerris Cooper. The network helps show where Kerris Cooper may publish in the future.
Co-authorship network of co-authors of Kerris Cooper
This figure shows the co-authorship network connecting the top 25 collaborators of Kerris Cooper.
A scholar is included among the top collaborators of Kerris Cooper based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Kerris Cooper. Kerris Cooper is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Cooper, Kerris & John Hills. (2021). The Conservative Governments’ Record on Social Security: Policies, Spending and Outcomes, May 2015 to pre-COVID 2020. London School of Economics and Political Science Research Online (London School of Economics and Political Science).2 indexed citations
4.
Cooper, Kerris & Kitty Stewart. (2020). Does Household Income Affect children’s Outcomes? A Systematic Review of the Evidence. Child Indicators Research. 14(3). 981–1005.162 indexed citations breakdown →
5.
Cooper, Kerris & Kitty Stewart. (2020). Does household income affect children’s outcomes? A systematic review of the evidence. London School of Economics and Political Science Research Online (London School of Economics and Political Science).1 indexed citations
McKnight, Abigail & Kerris Cooper. (2020). The National Living Wage and falling earnings inequality. London School of Economics and Political Science Research Online (London School of Economics and Political Science).1 indexed citations
Stewart, Kitty, Kerris Cooper, & Isabel Shutes. (2019). What does Brexit mean for social policy in the UK? An exploration of the potential consequences of the 2016 referendum for public services, inequalities and social rights. London School of Economics and Political Science Research Online (London School of Economics and Political Science).1 indexed citations
Lupton, Ruth, et al.. (2018). City-region devolution in England. London School of Economics and Political Science Research Online (London School of Economics and Political Science).5 indexed citations
13.
Cooper, Kerris & Kitty Stewart. (2017). Does Money Affect Children's Outcomes? An update. London School of Economics and Political Science Research Online (London School of Economics and Political Science).24 indexed citations
Cooper, Kerris & Kitty Stewart. (2015). Does money in adulthood affect adult outcomes. London School of Economics and Political Science Research Online (London School of Economics and Political Science).19 indexed citations
Cooper, Kerris & Kitty Stewart. (2013). Does money affect children's outcomes?. BMJ Case Reports.1 indexed citations
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.