New Medical Studies, Same Old Politics: The Effects of Anti-Black Racism on Penetrative Trauma Research
Bibliographic record
Abstract
The effects of medical racism on health outcomes of Black people in the U.S. are well recorded in prominent medical journals and governmental study data. Despite this documentation, there has yet to be broad structural change addressing the multiple oppressive systems intersecting to create adverse outcomes for Black people. Consequently, trust in medicine and medical practitioners continues to be low, which impacts the relationship between Black people and dominant institutions of medicine, including medical research. In this paper, I analyze the ethics of a forthcoming study on penetrative wound treatment from Temple University Hospital in Philadelphia. Using Franz Fanon’s analysis of medicine as a form of colonial practice and Dorothy Roberts’ analysis of the biological reduction of social inequities to problems of Black people themselves, I argue that the Philadelphia Immediate Transport in Penetrating Trauma Trial, or PIPT study 1) fails to meet the ethical requirement of treating study participants as human beings; 2) fails to engage with deep, structural inequities that produce higher rates of gun violence in communities from which study participants will be drawn; and 3) functions to reinforce stereotypes of Black men as violent and as thus to blame for the violence they face individually and at a community level. Without addressing the intersectional, structural, and interpersonal forms of oppression framing studies like the PIPT, I contend that medical researchers, medical practitioners, and policy makers cannot fully appreciate the extent to which race and anti-Black racism function to prevent the health and well-being of Black people.
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 | 0.299 | 0.336 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.015 | 0.080 |
| Scholarly communication | 0.016 | 0.019 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.006 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".