Kevin McDermott

814 total citations
64 papers, 456 citations indexed

About

Kevin McDermott is a scholar working on Sociology and Political Science, Genetics and Political Science and International Relations. According to data from OpenAlex, Kevin McDermott has authored 64 papers receiving a total of 456 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Sociology and Political Science, 18 papers in Genetics and 14 papers in Political Science and International Relations. Recurrent topics in Kevin McDermott's work include Genetic and phenotypic traits in livestock (18 papers), Eastern European Communism and Reforms (15 papers) and Genetic Mapping and Diversity in Plants and Animals (12 papers). Kevin McDermott is often cited by papers focused on Genetic and phenotypic traits in livestock (18 papers), Eastern European Communism and Reforms (15 papers) and Genetic Mapping and Diversity in Plants and Animals (12 papers). Kevin McDermott collaborates with scholars based in Ireland, Canada and United Kingdom. Kevin McDermott's co-authors include Anna Majury, N. McHugh, Paul Hynds, R. Stephen Brown, D.P. Berry, T. Pabiou, E. Wall, Matthew Stibbe, Corinne J. Schuster‐Wallace and Sarah Dickson‐Anderson and has published in prestigious journals such as The Science of The Total Environment, Water Research and Environmental Pollution.

In The Last Decade

Kevin McDermott

56 papers receiving 423 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Kevin McDermott Ireland 12 149 104 73 71 58 64 456
André Markemann Germany 12 99 0.7× 59 0.6× 26 0.4× 103 1.5× 8 0.1× 28 521
Nadhem Mtimet Kenya 13 30 0.2× 20 0.2× 32 0.4× 65 0.9× 9 0.2× 56 583
John Laws United Kingdom 15 63 0.4× 26 0.3× 10 0.1× 106 1.5× 28 0.5× 43 574
Stacy Sneeringer United States 11 17 0.1× 23 0.2× 15 0.2× 36 0.5× 6 0.1× 34 393
Danielle Nierenberg United States 7 16 0.1× 19 0.2× 19 0.3× 23 0.3× 5 0.1× 13 305
Simeon Kaitibie United States 14 10 0.1× 50 0.5× 31 0.4× 79 1.1× 7 0.1× 43 482
Alison Burrell United Kingdom 14 21 0.1× 16 0.2× 10 0.1× 153 2.2× 16 0.3× 69 580
M. Hoffmann Germany 13 44 0.3× 8 0.1× 107 1.5× 50 0.7× 10 0.2× 92 743
Levan Elbakidze United States 14 7 0.0× 36 0.3× 45 0.6× 49 0.7× 10 0.2× 50 414
Timothy O. Williams Ghana 17 26 0.2× 49 0.5× 22 0.3× 128 1.8× 16 0.3× 39 682

Countries citing papers authored by Kevin McDermott

Since Specialization
Citations

This map shows the geographic impact of Kevin McDermott'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 Kevin McDermott with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin McDermott more than expected).

Fields of papers citing papers by Kevin McDermott

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kevin McDermott. 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 Kevin McDermott. The network helps show where Kevin McDermott may publish in the future.

Co-authorship network of co-authors of Kevin McDermott

This figure shows the co-authorship network connecting the top 25 collaborators of Kevin McDermott. A scholar is included among the top collaborators of Kevin McDermott 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 Kevin McDermott. Kevin McDermott is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Hynds, Paul, et al.. (2024). Development of a “big data” groundwater microbial contamination index and spatial comparisons with enteric infection rates in southern Ontario. The Science of The Total Environment. 947. 174408–174408. 3 indexed citations
4.
Conington, J., et al.. (2022). Across‐country genetic evaluation of meat sheep from Ireland and the United Kingdom. Journal of Animal Breeding and Genetics. 139(3). 342–350. 5 indexed citations
5.
McDermott, Kevin, et al.. (2022). Sources of microbial contamination in the watershed and coastal zone of Soufriere, St. Lucia. Environmental Monitoring and Assessment. 194(3). 225–225. 7 indexed citations
6.
Dickson‐Anderson, Sarah, Anna Majury, Kevin McDermott, et al.. (2021). Exploration of E. coli contamination drivers in private drinking water wells: An application of machine learning to a large, multivariable, geo-spatio-temporal dataset. Water Research. 197. 117089–117089. 23 indexed citations
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Conington, J., T. Pabiou, Kevin McDermott, et al.. (2020). Genetic analyses of live weight and carcass composition traits in purebred Texel, Suffolk and Charollais lambs. animal. 14(5). 899–909. 14 indexed citations
9.
McGovern, F., et al.. (2020). Phenotypic factors associated with lamb live weight and carcass composition measurements in an Irish multi-breed sheep population1. Translational Animal Science. 4(4). 14 indexed citations
10.
Hynds, Paul, R. Stephen Brown, Corinne J. Schuster‐Wallace, et al.. (2020). Analysis of a large spatiotemporal groundwater quality dataset, Ontario 2010–2017: Informing human health risk assessment and testing guidance for private drinking water wells. The Science of The Total Environment. 738. 140382–140382. 39 indexed citations
11.
Sanderson, Haley, Rodrigo Ortega Polo, Kevin McDermott, et al.. (2019). Quantification and Multidrug Resistance Profiles of Vancomycin-Resistant Enterococci Isolated from Two Wastewater Treatment Plants in the Same Municipality. Microorganisms. 7(12). 626–626. 11 indexed citations
12.
Sanderson, Haley, Rodrigo Ortega Polo, Kevin McDermott, et al.. (2019). Comparison of biochemical and genotypic speciation methods for vancomycin-resistant enterococci isolated from urban wastewater treatment plants. Journal of Microbiological Methods. 161. 102–110. 9 indexed citations
13.
Berry, D.P., Jim O’Donovan, N. McHugh, et al.. (2018). Aneuploidy in dizygotic twin sheep detected using genome-wide single nucleotide polymorphism data from two commonly used commercial vendors. animal. 12(12). 2462–2469. 9 indexed citations
14.
McHugh, N., F. McGovern, P. Creighton, et al.. (2018). Mean difference in live-weight per incremental difference in body condition score estimated in multiple sheep breeds and crossbreds. animal. 13(3). 549–553. 18 indexed citations
15.
Berry, D.P., et al.. (2017). Imputation of non-genotyped sheep from the genotypes of their mates and resulting progeny. animal. 12(2). 191–198. 9 indexed citations
16.
McHugh, N., E. Wall, T. Pabiou, et al.. (2016). Genetic parameters for lameness, mastitis and dagginess in a multi-breed sheep population. animal. 11(6). 911–919. 22 indexed citations
17.
McDermott, Kevin & Matthew Stibbe. (2010). Stalinist terror in Eastern Europe: elite purges and mass repression. Manchester University Press eBooks. 4 indexed citations
18.
McDermott, Kevin, et al.. (2007). Exploring who we are in the context of global reforms in education: the Second Level Support Service in conversation. Irish Educational Studies. 26(3). 239–252. 3 indexed citations
19.
McDermott, Kevin, et al.. (2003). Stalin's terror : high politics and mass repression in the Soviet Union. Palgrave Macmillan eBooks. 10 indexed citations
20.
McDermott, Kevin. (1992). Essay in Historiography. Labour History Review. 57(3). 37–58. 2 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.

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