Building Family Relationships With Inherited Stepgrandparents
Bibliographic record
Abstract
Objective To understand how, and under what conditions, stepgrandchildren build and maintain familial ties with inherited stepgrandparents, using symbolic interaction theory as a lens. Background High rates of divorce and remarriage coupled with increases in longevity suggest that more children have stepgrandparent relationships than ever before. Stepgrandparents, who are the parents of a stepparent (i.e., inherited stepgrandparents), have been hypothesized to play key roles in shaping stepfamily life, but little is known about how stepgrandchildren develop close, family‐like intergenerational steprelationships after a parent's remarriage. Method Forty‐three adult stepgrandchildren (15 men, 28 women) were interviewed about their relationships with 131 inherited stepgrandparents. Grounded theory procedures were used to collect and analyze the data. Results Four key processes were identified that served as markers of kinship and facilitated the development of close familial ties: (a) stepgrandchildren feeling affectionate toward middle‐generation stepparents, (b) stepgrandparents engaging in affinity‐building efforts, (c) stepgrandchildren evaluating affinity‐building efforts favorably, and (d) biological parents using age‐effective strategies to facilitate relationship development. Conclusion Stepgrandchildren actively construct their relationships with stepgrandparents using symbols available to them, which are influenced by third parties such as parents and stepparents. When stepgrandchildren claim stepgrandparents as family, they perceive benefits. Implications Intergenerational stepfamily relationships may be valuable resources for children whose parents divorce and remarry.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".