Don’t Wait Till Tomorrow: How to Support Underrepresented Undergraduate HIV Researchers Today From the Voices of Emerging Leaders
Bibliographic record
Abstract
Undergraduate, underrepresented minority (URM) scholars must be comprehensively supported by the current HIV workforce to lead the future of HIV research. This commentary elaborates on the lived experience and outcomes of alumni from an undergraduate HIV research program and is written by alumni themselves. Undergraduate research enrichment programs for URM scholars are consistently deprioritized, underfunded, underresourced, and scrutinized. We seek to remind our audience of the outstanding contributions made to HIV and public health by URM scholars from these programs, such as the Student Opportunities for AIDS/HIV Research (SOAR) program. SOAR students and alumni report 95% placement in Masters, Doctoral, and Professional graduate programs, 100 conference presentations, and 34 publications within 3 years of the program's onset. Ultimately, this commentary speaks to the necessity of not only supporting URM researchers but also having a sustainable succession plan for advancing HIV research and programming. We recommend incorporating (a) critical health equity curriculum, (b) multidirectional mentorship, and (c) paid labor, which are crucial to tailor to URM scholars for their success and retention in research. Waiting to support the next generation of HIV researchers denies the urgency to respond to this intersectional public health issue-inaction is not an option.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".