David T. Smith

48 papers receiving 567 citations

Peers

David T. Smith
Comparison fields: 5 of 115
  • Health 156
  • Computer Science Applications 54
  • Modeling and Simulation 23
  • Sociology and Political Science 154
  • Statistics, Probability and Uncertainty 21
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Cristina Pulido Spain
Elizabeth Buchanan United States
Emmanuel Koku United States
Per Engzell United Kingdom
A. G. Howson United States
Monica Pivetti Italy
Heather Ames Norway
Jacob T.N. Young United States
Chris Campbell Australia
Romy van der Lee Netherlands
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Citations per year

Countries citing papers authored by David T. Smith

Since Specialization
Citations

This map shows the geographic impact of David T. Smith'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 David T. Smith with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David T. Smith more than expected).

Fields of papers citing papers by David T. Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David T. Smith. 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 David T. Smith. The network helps show where David T. Smith may publish in the future.

Co-authors

The 25 scholars most cited alongside David T. Smith, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David T. Smith Line = papers co-authored together David T. Smith links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201556
2 201855
3 202144
4 201742
5 201433
6 200733
7 201927
8 201525
9 201425
10
The Rise and Fall of Monetarism
199125
11 198424
12 200121
13
From Boom to Bust
199320
14 201318
15 197715
16 201715
17
From Boom to Bust: Trial and Error in British Economic Policy
199212
18 197211
19 201910
20 20219

About David T. Smith

David T. Smith is a scholar working on Sociology and Political Science, Political Science and International Relations, Information Systems, Health and Education, having authored 61 papers that have together received 620 indexed citations. Recurring topics across this work include Vaccine Coverage and Hesitancy (8 papers), Religion and Society Interactions (7 papers), American Constitutional Law and Politics (7 papers), Information Systems Education and Curriculum Development (6 papers), Sensor Technology and Measurement Systems (4 papers), Teaching and Learning Programming (4 papers), Online and Blended Learning (3 papers) and Experimental Learning in Engineering (3 papers). The work is most often cited by research in Health (156 citations), Computer Science Applications (54 citations), Modeling and Simulation (23 citations), Sociology and Political Science (154 citations) and Statistics, Probability and Uncertainty (21 citations). David T. Smith has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Azad Ali, Katie Attwell, Uwana Evers, Paul Ward, A. M. Glazer, Paul D. Groves, David J. Rogers, Patricia McGuiggan, K. L. Johnson and Johannes Urpelainen. Their work appears in journals such as Journal of Information Technology Education Innovations in Practice, Politics, Vaccine, PS Political Science & Politics and Journal of sociology.

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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