Responsive social support to disclosures of racial discrimination: Expectations and implications for well-being.
Bibliographic record
Abstract
OBJECTIVES: Social support helps people of color (POC) cope with stressors such as racial discrimination. Yet when POC disclose lived experiences of racism, confidants may fail to provide support that meets disclosers' emotional needs. Drawing on theories of shared reality and emotion reappraisal, we compare two emotion-focused social support approaches: validation (conveying that recipients' feelings or responses are appropriate) and reframing (seeking to reduce recipients' distress by offering a more positive perspective). METHOD: Two POC samples of Canadian young adults (35% South Asian, 32% East Asian, 9% Black, 8% Southeast Asian, 7% Middle Eastern, 2% Latino/a/e, 1% Indigenous, 6% other; 78% women, 19% men, 2% nonbinary; mean age = 19.9) recalled a lived experience of racism then were randomly assigned to imagine disclosing it to a White or same-race confidant. RESULTS: In Study 1 (N = 430), POC rated validation as more helpful than reframing and forecasted larger gaps between desired and expected support from White than same-race confidants. Study 2 (N = 651) found that (a) experiences of racism are disclosed to same-race and White confidants more often than other groups and (b) imagining a confidant's reframing (vs. validating) response led to worse overall affect, less perceived responsiveness, less racial shared reality, and more rumination. In both studies, the gap between validation and reframing on perceived support increased for experiences that participants more strongly attributed to race, especially when disclosed to White confidants. CONCLUSIONS: Implications for providing responsive emotional support for lived experiences of racism are discussed. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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 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".