Unique Influences on American Indian Relationship Quality: An American-Indian and Caucasian Comparison
Bibliographic record
Abstract
We compare American Indians and Caucasians on the influence of family-of-origin quality on the adult-children’s later romantic relationship quality. Using data from the RELATE, 341 American Indians and 341 Caucasian participants were analyzed using group comparison methods. Structural equation modeling demonstrated that, overall, the perceived impact of family-of-origin mediated the significant influence of family-of-origin on later adult romantic relationship stability and satisfaction. However, for American Indians, the quality of the father-child relationship did not directly or indirectly influence the child’s later adult relationship quality. Still, a large portion of the father-child and mother-child relationship and quality of the parent’s marriage explains a large portion of the variance of the child’s overall perception of the impact of his or her family. Additionally, group comparison methods demonstrated that American Indians generally reported lower values on family-of-origin quality measures and relationship stability. However, they had comparable relationship satisfaction and father-child relationship quality ratings. Findings suggest that historical trauma and collectivistic cultural patterns may at least partially explain these observations. Several suggestions are made to guide interventions for American Indian families.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".