Tom Mieczkowski

1.4k total citations
47 papers, 1.1k citations indexed

About

Tom Mieczkowski is a scholar working on Toxicology, Sociology and Political Science and Political Science and International Relations. According to data from OpenAlex, Tom Mieczkowski has authored 47 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Toxicology, 15 papers in Sociology and Political Science and 7 papers in Political Science and International Relations. Recurrent topics in Tom Mieczkowski's work include Forensic Toxicology and Drug Analysis (16 papers), Crime Patterns and Interventions (10 papers) and Policing Practices and Perceptions (7 papers). Tom Mieczkowski is often cited by papers focused on Forensic Toxicology and Drug Analysis (16 papers), Crime Patterns and Interventions (10 papers) and Policing Practices and Perceptions (7 papers). Tom Mieczkowski collaborates with scholars based in United States, Canada and Russia. Tom Mieczkowski's co-authors include Kim Michelle Lersch, Éric Beauregard, Eric D. Wish, Michael Krüger, Fritz Pragst, Carl M. Selavka, Raymond C. Kelly, Christine S. Sellers, Yuji Nakahara and Ruri Kikura and has published in prestigious journals such as Life Sciences, Forensic Science International and Aggression and Violent Behavior.

In The Last Decade

Tom Mieczkowski

46 papers receiving 953 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tom Mieczkowski United States 19 446 334 234 217 213 47 1.1k
David F. Musto United States 12 295 0.7× 68 0.2× 43 0.2× 319 1.5× 185 0.9× 37 1000
Katy Holloway United Kingdom 18 459 1.0× 46 0.1× 52 0.2× 608 2.8× 341 1.6× 44 1.2k
Robert Ralphs United Kingdom 13 296 0.7× 110 0.3× 36 0.2× 145 0.7× 109 0.5× 34 557
James Chiesa United States 15 368 0.8× 28 0.1× 23 0.1× 222 1.0× 415 1.9× 41 1.3k
Eric L. Sevigny United States 15 264 0.6× 33 0.1× 49 0.2× 444 2.0× 146 0.7× 35 988
Anne Line Bretteville‐Jensen Norway 18 132 0.3× 154 0.5× 8 0.0× 493 2.3× 205 1.0× 69 943
Dina Perrone United States 12 356 0.8× 33 0.1× 23 0.1× 122 0.6× 157 0.7× 20 752
Helene Wells Australia 13 153 0.3× 28 0.1× 52 0.2× 63 0.3× 224 1.1× 25 784
Julia A. Dilley United States 20 168 0.4× 33 0.1× 14 0.1× 325 1.5× 197 0.9× 44 1.3k
Susan Beckerleg United Kingdom 15 142 0.3× 85 0.3× 16 0.1× 213 1.0× 84 0.4× 32 566

Countries citing papers authored by Tom Mieczkowski

Since Specialization
Citations

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

Fields of papers citing papers by Tom Mieczkowski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tom Mieczkowski

This figure shows the co-authorship network connecting the top 25 collaborators of Tom Mieczkowski. A scholar is included among the top collaborators of Tom Mieczkowski 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 Tom Mieczkowski. Tom Mieczkowski 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
1.
Mieczkowski, Tom & Éric Beauregard. (2012). Interactions between disinhibitors in sexual crimes: additive or counteracting effects?. Journal of Crime and Justice. 35(3). 395–411. 12 indexed citations
2.
Beauregard, Éric & Tom Mieczkowski. (2012). Risk Estimations of the Conjunction of Victim and Crime Event Characteristics on the Lethal Outcome of Sexual Assaults. Violence and Victims. 27(4). 470–486. 32 indexed citations
3.
Selavka, Carl M., et al.. (2010). Fatty acid ethyl ester concentrations in hair and self-reported alcohol consumption in 644 cases from different origin. Forensic Science International. 196(1-3). 111–117. 50 indexed citations
4.
5.
Mieczkowski, Tom. (2010). Urinalysis and hair analysis for illicit drugs of driver applicants and drivers in the trucking industry. Journal of Forensic and Legal Medicine. 17(5). 254–260. 16 indexed citations
6.
Mieczkowski, Tom & Michael Krüger. (2007). Interpreting the color effect of melanin on cocaine and benzoylecgonine assays for hair analysis: Brown and black samples compared. Journal of Forensic and Legal Medicine. 14(1). 7–15. 17 indexed citations
7.
Lersch, Kim Michelle, et al.. (2005). Kids, Cops, Parents, and Teachers: Exploring Juvenile Attitudes toward Authority Figures. Digital Commons - University of South Florida (University of South Florida). 6(1). 79–6. 40 indexed citations
8.
Mieczkowski, Tom. (2004). Drug testing the police: some results of urinalysis and hair analysis in a major US metropolitan police force. Journal of Clinical Forensic Medicine. 11(3). 115–122. 8 indexed citations
9.
10.
Mieczkowski, Tom, et al.. (2001). The concentration of three anti-seizure medications in hair: the effects of hair color, controlling for dose and age. PubMed. 1(1). 2–2. 13 indexed citations
11.
Mieczkowski, Tom. (2000). Is a “color effect” demonstrated for hair analysis of carbamazepine?. Life Sciences. 67(1). 39–43. 7 indexed citations
12.
Mieczkowski, Tom, et al.. (2000). Statistical examination of hair color as a potential biasing factor in hair analysis. Forensic Science International. 107(1-3). 13–38. 28 indexed citations
13.
Kelly, Raymond C., et al.. (2000). Hair analysis for drugs of abuse.. Forensic Science International. 107(1-3). 63–86. 52 indexed citations
14.
Kikura, Ruri, Yuji Nakahara, Tom Mieczkowski, & Franco Tagliaro. (1997). Hair analysis for Drug Abuse XV. Disposition of 3,4-methylenedioxymethamphetamine (MDMA) and its related compounds into rat hair and application to hair analysis for MDMA abuse. Forensic Science International. 84(1-3). 165–177. 40 indexed citations
15.
Mieczkowski, Tom, et al.. (1997). A research note: an analysis of RIA and GC/MS split hair samples from the New Orleans pretrial diversion program. Forensic Science International. 84(1-3). 67–73. 5 indexed citations
16.
Mieczkowski, Tom. (1997). Distinguishing passive contamination from active cocaine consumption: assessing the occupational exposure of narcotics officers to cocaine. Forensic Science International. 84(1-3). 87–111. 29 indexed citations
17.
Mieczkowski, Tom. (1995). A research note: the outcome of GC/MS/MS confirmation of hair assays on 93 cannabinoid (+) cases. Forensic Science International. 70(1-3). 83–91. 36 indexed citations
18.
Mieczkowski, Tom, et al.. (1993). An evaluation of patterns of racial bias in hair assays for cocaine: black and white arrestees compared. Forensic Science International. 63(1-3). 85–98. 28 indexed citations
19.
Mieczkowski, Tom. (1992). New Approaches in Drug Testings: A Review of Hair Analysis. The Annals of the American Academy of Political and Social Science. 521(1). 132–150. 14 indexed citations
20.
Mieczkowski, Tom. (1990). Drugs, Crime, and the Failure of American Organized Crime Models. International Journal of Comparative and Applied Criminal Justice. 14(1-2). 97–106. 4 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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