Growing up with foster siblings: Exploring the impacts of fostering on the children of foster parents
Bibliographic record
Abstract
Growing up with foster siblings, the children of foster parents have experienced fostering from a different perspective which has continued to impact them throughout their lives. In this qualitative study, the experiences of 12 daughters of foster parents (aged 20–33 years) are explored, along with how they cope with their fostering experiences. Open-ended interviews, demographic questionnaires, object sharing, photographing the object, photo-feedback, and memo-writing were included within the data collection process. Data analysis included initial coding, focused coding, and memo-writing. Dedoose, a data management system, was used to assist in analysing the multiple data sources. Findings reveal that the daughters of foster parents are exposed to multiple foster sibling relationships due to the temporary nature of foster care. To protect their emotional well-being, these participants become apprehensive about developing relationships with new foster siblings, as well as with friends and romantic partners. Participating daughters sought emotional support from their mothers who established a strong, stable, and supportive relationship with them. Recommendations for foster parents and social workers are suggested.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".