Dismantling "Race" in Health Research
Bibliographic record
Abstract
In this era of confronting racism in public space, it is critical to keep addressing the covert systemic racism in the healthcare system. We want to bring attention to the continued unscientific practice of race-based medicine and the absurdity of treating race as a biological indicator in the 21st century. We believe race is a social construct that does not qualify as a scientific biological indicator for predicting health outcomes. In this paper, we first present arguments for inappropriate use of race in health research and then discuss alternative explanations for health disparity findings that use race as a predictor. Our main concern centers on two specific aspects of the concept of "race": (1) its fundamental lack of scientific basis as a predictor for health outcomes, (2) the misguided narrative that the term creates, placing the onus of racial discrimination on the victim, instead of highlighting the act of discrimination and the role researchers play in actively reinforcing racism when using "race" as a variable. We conclude by proposing that "race" be replaced by the variable "racism" in health.
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 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 | 0.065 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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 teacher head, 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".