How Do Acculturation, Maternal Connectedness, and Mother-Daughter Sexual Communication Affect Asian American Daughters’ Sexual Initiation
Bibliographic record
Abstract
Purpose: There was a growth of approximately ten million Asian American individuals in the United States between 2000 and 2015. Asian Americans have conservative values surrounding sexual health and sexual communication is a cultural taboo. Researchers have shown discrepancies on whether the level of acculturation influences Asian mother-daughter sexual communication. In other minority populations there is evidence that a connected mother–daughter relationship increases sexual communication and delays sexual initiation. The purpose of this study was to examine whether motherdaughter connectedness and level of acculturation predict sexual communication in turn affecting the age of female Asian emerging adult’s sexual initiation. Methods: This was a longitudinal, secondary analysis of AddHealth examining whether mother-daughter connectedness and level of acculturation predict sexual communication. There were 243 Asian American mother-daughter dyads in Wave I with linked data in Wave III who were included in the study. Acculturation, connectedness, and sexual communication were all measured using interval level data. Results: Connectedness did not significantly contribute to the relationship between any of the concepts. Although it was predicted that sexual communication would delay initiation, the opposite was found. Also, communication mediated the relationship between acculturation and initiation. Conclusions: Further studies are needed to explore how connectedness is defined by Asian American mother-daughter dyads. In addition, more detailed operational definitions of acculturation and communication are needed, specifically the timing of sexual communication.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".