Laboratory-based inequity in thrombosis and hemostasis: review of the evidence
Bibliographic record
Abstract
The concept of normal in hematology, similar to that in other areas of medicine, is anchored to the perspective of those setting the standard. This means that several laboratory reference intervals and approaches to the conditions of thrombosis and hemostasis are influenced by the vantage point of those in power. Structural inequity, including systemic racism and sexism, can lead to inappropriate normalization of disease states, such as anemia or iron deficiency, or delayed diagnoses, such as in von Willebrand disease. This review will focus on how laboratory reference intervals perpetuate the cycles of inequity in care of patients with disorders of thrombosis and hemostasis. We provide examples and case studies in maternal mortality as well as in disorders such as von Willebrand disease and iron deficiency, question physiology versus pathophysiology, acknowledge the distinction between social constructs and biologic influence, and highlight opportunities for much-needed restructuring in areas such as defining anemia and iron deficiency.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".