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.
Self-efficacy and music performance
2006251 citationsGary E. McPherson et al.Psychology of Musicprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Gary E. McPherson
Since
Specialization
Citations
This map shows the geographic impact of Gary E. McPherson'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 Gary E. McPherson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gary E. McPherson more than expected).
Fields of papers citing papers by Gary E. McPherson
This network shows the impact of papers produced by Gary E. McPherson. 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 Gary E. McPherson. The network helps show where Gary E. McPherson may publish in the future.
Co-authorship network of co-authors of Gary E. McPherson
This figure shows the co-authorship network connecting the top 25 collaborators of Gary E. McPherson.
A scholar is included among the top collaborators of Gary E. McPherson 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 Gary E. McPherson. Gary E. McPherson is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
McPherson, Gary E.. (2017). Floating on a Sea of Funny Money: An Analysis of Money Laundering Through Miami Real Estate and the Federal Government’s Attempt to Stop it. 26(1). 159.4 indexed citations
Schubert, Emery, Sam Ferguson, David Taylor, & Gary E. McPherson. (2012). Continuous Response to Music using Discrete Emotion Faces. Minerva Access (University of Melbourne).4 indexed citations
Schubert, Emery, et al.. (2011). Sonification of Emotion I: Film Music. SMARTech Repository (Georgia Institute of Technology).5 indexed citations
14.
Davidson, Jane W., Robert Faulkner, & Gary E. McPherson. (2009). Motivating musical learning. Psychologist. 22(12). 1026–1029.3 indexed citations
15.
McPherson, Gary E.. (2007). Personal reflections on music education research. Lund University Publications (Lund University).1 indexed citations
16.
McPherson, Gary E.. (2004). It's the End of the World as We Know It (and I Feel Fine): Rent Regulation in New York City and the Unanswered Questions of Market and Society. Fordham law review. 72(4). 1125.2 indexed citations
17.
McPherson, Gary E.. (2000). Commitment and Practice: Key Ingredients for Achievement During the Early Stages of Learning a Musical Instrument*. Bulletin of the Council for Research in Music Education. 122–127.42 indexed citations
18.
McPherson, Gary E.. (1997). Cognitive Strategies and Skill Acquisition in Musical Performance.. Bulletin of the Council for Research in Music Education.28 indexed citations
19.
McPherson, Gary E.. (1996). 5 ASPECTS OF MUSICAL PERFORMANCE AND THEIR CORRELATES. Bulletin of the Council for Research in Music Education.20 indexed citations
20.
McPherson, Gary E.. (1989). Cognitive mediational processes and positive motivation: Implications of educational research for music teaching and learning. Australian journal of music education/Australian journal of music education (Online). 3.2 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.