David Joel Goodman
Papers
1
Total Citations
3
H-Index
1
About
David Joel Goodman is a researcher whose work critically examines the intersection of information science and automated content classification. His primary research area focuses on the evaluation of algorithmic performance in identifying open access (OA) scholarly articles, a niche but vital domain for ensuring the integrity of digital repositories and bibliometric analyses. Goodman’s most cited paper, "Evaluation of Algorithm Performance on Identifying OA" (2005, 3 citations), stands out for its rigorous signal-detection analysis of a robot’s accuracy in tagging OA content. By manually verifying the robot’s classifications, he demonstrated a significant tendency to overcode for OA—in one biology sample, 40% of identified OA articles were false positives. This contribution highlighted critical flaws in automated metadata generation, underscoring the need for human oversight in large-scale indexing. Though his citation count is modest, Goodman’s work has practical implications for librarians, data scientists, and publishers striving for reliable OA discovery. His meticulous methodology serves as a cautionary tale for researchers relying on algorithmic tools, cementing his role as a thoughtful evaluator of information systems.
Research Focus
Key Achievements
Top Papers
- 1Evaluation of Algorithm Performance on Identifying OA3 citations · 2005