Differences in the Communication of Affect: Members of the Same Race Versus Members of a Different Race
Bibliographic record
Abstract
This study examined African American and Caucasian individuals'ability to recognize facial expressions and vocal prosody of predominately Caucasian stimuli at three age groups: children's pictures and voices, young adults' pictures and voices, and older adults'pictures and voices. The Diagnostic Assessment of Non- verbal Accuracy 2 (DANVA 2) and the Carolina Older Adult Test of Nonverbal Communication (COAT-NC) were used to measure these skills. The results indicate race is a significant factor in the interpretation of emotion of facial expressions and prosodic features.. They suggest that individuals from a specific ethnic group are more accurate in decoding emotional cues from stimulus-containing individuals within the same ethnic group. Caucasians were not necessarily better than African Americans decoding communication of affect, but were more successful at interpreting the emotions of individuals within their ethnic group. The results indicate potential for miscommunications between African Americans and Caucasians.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".