Pan-African identity, psychological well-being, and mental health among African Americans
Bibliographic record
Abstract
Studies show that racial and ethnic identity can significantly improve mental health and well-being among marginalized ethnoracial groups who experience racism and discrimination. However, the relationships between Pan-African identity, psychological well-being, and mental health have received less attention. Using a national sample of African American adults, I examine whether Pan-African identity impacts psychological well-being and self-rated mental health. The results show that respondents who feel closer towards members of the African diaspora and Black people in Africa and prefer Pan-African labels have better self-rated mental health and higher levels of self-esteem. Moreover, the analysis finds that respondents who prefer Pan-African labels have higher levels of mastery. Although self-esteem explains the self-rated mental health benefits of both Pan-African closeness and Pan-African label preferences, only mastery explains the relationship between Pan-African label preferences and self-rated mental health. This study demonstrates the possible psychological benefits of a globalized identity for marginalized groups in Eurocentric contexts.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".