Perceived microaggressions and quality of life: the mediating role of personal resources and social support among people with African migration background in Germany
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In contemporary discourse, microaggressions are not mere fleeting occurrences but pervasive daily experiences that significantly influence individual and collective well-being. This current study delves into the role of personal resources and social support as mediators in the relationship between microaggressions and quality of life. The study analyses cross-sectional data from 604 African migrants in Germany, employing Structural Equation Modelling techniques. Five direct associations were examined alongside three separate mediation analyses to evaluate the predictive effect of microaggressions on quality of life through personal resources, social support, and the combined influence of both. The results indicate a negative association between microaggressions, personal resources, social support, and quality of life. Microaggressions constrain personal resources and social support, thereby compromising quality of life, as evidenced by the attenuating effects observed in the mediation analyses. Furthermore, the serial mediation model highlights the distinct contributions of personal resources and social capital. The findings underscore the serialised nature of microaggression’s impact on quality of life, suggesting that neither personal resources nor social support can fully mitigate its effects. This study posits that microaggressions manifest through migrants’ social interactions and exchanges, undermining personal resources and social support networks essential for enhancing their quality of life.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it