Academic Productivity Is Positively Correlated With Nonresearch Industry Earnings Across all Subspecialties Among Faculty Physicians Affiliated With Orthopaedic Surgery Fellowship Programs in the United States: A Retrospective Analysis
Bibliographic record
Abstract
BACKGROUND: Physician-industry transparency was solidified through the Physician Payments Sunshine Act in 2010, allowing greater examination. To date, little data exist regarding the association between academic productivity and industry earnings, especially across faculty affiliated with orthopaedic surgery fellowship subspecialities. This study examines the association of both individual faculty and program academic productivity on nonresearch lifetime industry earnings across all orthopaedic surgery subspecialty fellowship programs in the United States to understand potential relationships between academic productivity and industry earnings. METHODS: This retrospective study analyzes the potential association between academic productivity (H-index on Scopus) and nonresearch lifetime industry earnings (recorded from Open Payments Database in 2023 to 2024) across faculty at all nine major orthopaedic subspecialties in the United States. RESULTS: This analysis included 568 orthopaedic fellowship programs with 3,040 individual faculty physicians. Median individual physician lifetime earnings (n = 3,040) were $15,871.03 (mean: $392,019.25 ± $1,818,339.97; minimum to maximum: $0.00 to 52,150,069.08), and the median individual physician H-index was 11 (mean: 16.48 ± 16.29; minimum to maximum: 0 to 129). Median combined physician H-index per fellowship (n = 568 fellowships) was 67.5 (mean: 88.25 ± 81.89; minimum to maximum: 0 to 689), and median combined physician lifetime earnings was $375,081.18 (mean: $2,098,131.2 ± $5,282,741.17; minimum to maximum: $127.44 to $56,200,489.37). A weak positive correlation was observed between academic productivity and industry earnings at the individual level ( P < 0.001; Spearman rho: 0.345) with a moderate positive correlation at the fellowship level ( P < 0.001; Spearman rho: 0.467). The top 10% of faculty at orthopaedic surgery fellowships accounted for 81.75% of the nonresearch industry earnings, whereas the top 1% captured 34.86% of industry earnings. No notable difference was found in total nonresearch lifetime earnings ( P = 0.156) or H-index per fellowship ( P = 0.065) when stratified by geographic region of the fellowship program. CONCLUSION: There is a positive correlation between academic productivity and nonresearch industry lifetime earnings at both individual faculty and program levels across all subspecialties in United States orthopaedic surgery fellowships. However, regional differences among programs are not associated with academic productivity or industry earnings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".