Ethnic-racial identity and ethnic-racial socialization competency: How minoritized parents “walk the talk”.
Bibliographic record
Abstract
OBJECTIVES: Ethnic-racial identity (ERI) has important implications for individual psychosocial functioning as well as familial processes. For example, parents' ERI can shape children's developmental contexts through ethnic-racial socialization (ERS). Yet, existing research has tended to focus on the content or frequency of socialization messages themselves rather than on internal factors like socialization competence. Such competence, as reflected through confidence, skills, and stress, represents critical dimensions that permeate the socialization process and can impact the delivery of messages. The present study examines whether parents' ERI (i.e., private regard, centrality, exploration) is related to perceptions of their socialization competence. METHOD: = 9.14, 59.70% mothers) of adolescents between the ages of 10-18 were collected via Qualtrics panels. RESULTS: Across all parents, private regard, centrality, and ethnic-racial exploration were positively associated with perceived confidence and skills in engaging in ERS. Regard was additionally associated with lower socialization stress. CONCLUSIONS: The results point to consistent benefits of ERI in helping parents navigate ERS, furthering the understanding of ERI's developmental implications through parents' comfort with and ability to "walk the talk" with their children. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.001 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".