David M. Smallwood

3.1k total citations
85 papers, 1.9k citations indexed

About

David M. Smallwood is a scholar working on General Health Professions, Economics and Econometrics and Gender Studies. According to data from OpenAlex, David M. Smallwood has authored 85 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in General Health Professions, 21 papers in Economics and Econometrics and 18 papers in Gender Studies. Recurrent topics in David M. Smallwood's work include Food Security and Health in Diverse Populations (24 papers), Economics of Agriculture and Food Markets (19 papers) and Gender, Labor, and Family Dynamics (18 papers). David M. Smallwood is often cited by papers focused on Food Security and Health in Diverse Populations (24 papers), Economics of Agriculture and Food Markets (19 papers) and Gender, Labor, and Family Dynamics (18 papers). David M. Smallwood collaborates with scholars based in Australia, United States and United Kingdom. David M. Smallwood's co-authors include James R. Blaylock, Jayachandran N. Variyam, Biing‐Hwan Lin, Louis Irving, Steven T. Yen, Gary P. Anderson, Jim Black, Anastasia Hutchinson, Michelle Thompson and Steven Bozinovski and has published in prestigious journals such as SHILAP Revista de lepidopterología, American Journal of Respiratory and Critical Care Medicine and Radiology.

In The Last Decade

David M. Smallwood

81 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David M. Smallwood Australia 22 583 505 400 312 297 85 1.9k
Daniel Warm United Kingdom 16 1.8k 3.0× 83 0.2× 91 0.2× 417 1.3× 482 1.6× 30 2.7k
Gretchen Van Wye United States 17 886 1.5× 53 0.1× 246 0.6× 177 0.6× 715 2.4× 40 2.2k
Wen You United States 24 875 1.5× 36 0.1× 156 0.4× 224 0.7× 738 2.5× 121 2.0k
Danielle Gallegos Australia 26 821 1.4× 104 0.2× 60 0.1× 219 0.7× 1.1k 3.8× 152 2.4k
K. Allen Greiner United States 30 849 1.5× 198 0.4× 160 0.4× 333 1.1× 1.0k 3.4× 100 3.0k
Caroline Miller Australia 29 1.1k 1.8× 63 0.1× 56 0.1× 693 2.2× 492 1.7× 144 2.5k
Nigar Nargis United States 26 455 0.8× 76 0.2× 270 0.7× 1.2k 3.8× 371 1.2× 92 2.3k
Megan Ferguson Australia 23 582 1.0× 111 0.2× 122 0.3× 44 0.1× 647 2.2× 79 1.7k
J. Nicholas Bodor United States 17 1.1k 1.9× 224 0.4× 51 0.1× 55 0.2× 518 1.7× 30 2.0k

Countries citing papers authored by David M. Smallwood

Since Specialization
Citations

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

Fields of papers citing papers by David M. Smallwood

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David M. Smallwood

This figure shows the co-authorship network connecting the top 25 collaborators of David M. Smallwood. A scholar is included among the top collaborators of David M. Smallwood 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 David M. Smallwood. David M. Smallwood 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.
Ryan, Anna, et al.. (2020). Fully online OSCEs: A large cohort case study. MedEdPublish. 9(1). 214–214. 14 indexed citations
2.
Barmanray, Rahul, et al.. (2019). Ambiguous medical abbreviation study: challenges and opportunities. Internal Medicine Journal. 50(9). 1073–1078. 13 indexed citations
3.
Cheong, Jeanie L.Y., John D. Wark, Michael M.H. Cheung, et al.. (2019). Impact of extreme prematurity or extreme low birth weight on young adult health and well-being: the Victorian Infant Collaborative Study (VICS) 1991–1992 Longitudinal Cohort study protocol. BMJ Open. 9(5). e030345–e030345. 15 indexed citations
4.
Liew, Danny, et al.. (2018). Benefit of targeted, pharmacist‐led education for junior doctors in reducing prescription writing errors – a controlled trial. Journal of Pharmacy Practice and Research. 48(1). 26–35. 12 indexed citations
5.
Duan, Mubing, Daniel Steinfort, David M. Smallwood, et al.. (2015). CD11b immunophenotyping identifies inflammatory profiles in the mouse and human lungs. Mucosal Immunology. 9(2). 550–563. 96 indexed citations
6.
Hutchinson, Anastasia, Jim Black, Michelle Thompson, et al.. (2009). Identifying viral infections in vaccinated Chronic Obstructive Pulmonary Disease (COPD) patients using clinical features and inflammatory markers. Influenza and Other Respiratory Viruses. 4(1). 33–39. 9 indexed citations
7.
Bozinovski, Steven, Anastasia Hutchinson, Michelle Thompson, et al.. (2007). Serum Amyloid A Is a Biomarker of Acute Exacerbations of Chronic Obstructive Pulmonary Disease. American Journal of Respiratory and Critical Care Medicine. 177(3). 269–278. 208 indexed citations
8.
Guthrie, Joanne F., Margaret Andrews, Elizabeth Frazão, et al.. (2007). Can Food Stamps Do More to Improve Food Choices? An Economic Perspective. RePEc: Research Papers in Economics. 9 indexed citations
9.
Oliveira, Victor, et al.. (2004). WIC and the Retail Price of Infant Formula. SSRN Electronic Journal. 10 indexed citations
10.
Lin, Biing‐Hwan, David M. Smallwood, William Hamilton, & Peter H. Rossi. (2004). Research Designs for Assessing the USDA???s Food Assistance and Nutrition Programs Outcomes, Part 2. Nutrition Today. 39(1). 40–45. 2 indexed citations
11.
Variyam, Jayachandran N., James R. Blaylock, David M. Smallwood, & P. Peter Basiotis. (1998). USDA's Healthy Eating Index and Nutrition Information. Technical Bulletins. 47 indexed citations
12.
Blaylock, James R., et al.. (1996). Dietary Fiber: Is Information the Key?. AgEcon Search (University of Minnesota, USA). 19(1). 24–30. 4 indexed citations
13.
Variyam, Jayachandran N., James R. Blaylock, & David M. Smallwood. (1995). Modeling Nutrient Intake: The Role of Dietary Information. Technical Bulletins. 1 indexed citations
14.
Smallwood, David M., et al.. (1994). Fiber: Not Enough of a Good Thing?. AgEcon Search (University of Minnesota, USA). 17(1). 23–29. 4 indexed citations
15.
Smallwood, David M., et al.. (1993). Changes in Food Consumption and Expenditures in 01/01 Low-Income American Households During the 1980's. AgEcon Search (University of Minnesota, USA). 2 indexed citations
16.
Blaylock, James R. & David M. Smallwood. (1986). U.S. Demand for Food: Household Expenditures, Demographics, and Projections. Technical Bulletins. 25 indexed citations
17.
Smallwood, David M., et al.. (1986). Forecasting Performance of Models Using the Box-Cox Transformation. Agricultural economics research. 38(4). 14–24. 3 indexed citations
18.
Blaylock, James R. & David M. Smallwood. (1985). Box-Cox Transformations and a Heteroscedastic Error Variance: Import Demand Equations Revisited. International Statistical Review. 53(1). 91–91. 4 indexed citations
19.
Smallwood, David M. & James R. Blaylock. (1984). Household Expenditures for Fruits, Vegetables, and Potatoes. Technical Bulletins. 7 indexed citations
20.
Smallwood, David M. & James R. Blaylock. (1981). Impact of Household Size and Income on Food Spending Patterns. Technical Bulletins. 18 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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