From singularity to plurality: The case for intersectionality in cardiothoracic surgery research
Bibliographic record
Abstract
Health services research is increasingly highlighting gaps in equitable cardiothoracic surgical care delivery, but the challenge translating these findings to interventions remains. Preventza and colleagues1 evaluated how the interplay between socioeconomic factors and sex may influence thoracic aortic surgery outcomes. Between 2000 and 2020, men undergoing thoracic aortic surgery at Baylor College of Medicine were associated with more favorable socioeconomic factors, reduced hospital length of stay, and lower rates of complications compared with women.
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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 | 0.236 | 0.191 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.014 | 0.010 |
| Science and technology studies | 0.016 | 0.104 |
| Scholarly communication | 0.026 | 0.058 |
| Open science | 0.005 | 0.049 |
| Research integrity | 0.008 | 0.019 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".