No Booster for Us! An Understanding of HBCU Students’ COVID-19 Booster Vaccine Hesitancy
Bibliographic record
Abstract
This exploratory study examines COVID-19 booster vaccine hesitancy among African American college students at a four-year Historically Black College and University (HBCU) in Maryland. Although limited in scope, this research has implications for students at other HBCUs because of the shared history and culture of the “Black experience” in the United States. The study was conducted using focus groups. Key findings lie in the areas of self-efficacy, gender, and health status couched in the context of African Americans’ generational distrust of government and science to serve their best interests. In terms of self-efficacy, the students stated by taking the initial vaccines, they had done enough to ward off severe COVID-19. A concern by gender was voiced about purported side effects of the vaccine experienced from the initial doses. Certainly, as with many young adults of all races, the students in the study had a sense of invincibility regarding their health. Overall, the findings indicate that government and health organizations need to work more purposively by listening to the young African Americans they seek to serve. This in turn could lead to the creation of more effective health messages to reach demographics and communities who view themselves as outliers from the larger society.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".