The Effect of Race and Income on Living Kidney Donation in the United States
Why this work is in the frame
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Bibliographic record
Abstract
Studies of racial disparities in access to living donor kidney transplantation focus mainly on patient factors, whereas donor factors remain largely unexamined. Here, data from the US Census Bureau were combined with data on all African-American and white living kidney donors in the United States who were registered in the United Network for Organ Sharing (UNOS) between 1998 and 2010 (N=57,896) to examine the associations between living kidney donation (LKD) and donor median household income and race. The relative incidence of LKD was determined in zip code quintiles ranked by median household income after adjustment for age, sex, ESRD rate, and geography. The incidence of LKD was greater in higher-income quintiles in both African-American and white populations. Notably, the total incidence of LKD was higher in the African-American population than in the white population (incidence rate ratio [IRR], 1.20; 95% confidence interval [95% CI], 1.17 to 1.24]), but ratios varied by income. The incidence of LKD was lower in the African-American population than in the white population in the lowest income quintile (IRR, 0.84; 95% CI, 0.78 to 0.90), but higher in the African-American population in the three highest income quintiles, with IRRs of 1.31 (95% CI, 1.22 to 1.41) in Q3, 1.50 (95% CI, 1.39 to 1.62) in Q4, and 1.87 (95% CI, 1.73 to 2.02) in Q5. Thus, these data suggest that racial disparities in access to living donor transplantation are likely due to socioeconomic factors rather than cultural differences in the acceptance of LKD.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it