An Exploratory Typology for Understanding Family-Relationship Issues in Kinship-Care Placements
Bibliographic record
Abstract
Family relationships are a distinctive feature of kinship-care placements, but very few studies have examined how the dynamics of these relationships affect the placement experience. This article does explore these dynamics and identifies some possible patterns, as experienced and reported by parents of children placed in kinship care. The findings presented here come from a qualitative study employing a life-story methodology, in which nine parents were interviewed on two occasions each. All of them had experienced the permanent placement of at least one of their children with a member of their extended family, under the direction of a government child-protection agency. Drawing from significant themes in parental narratives, particularly that of relationships, we analyzed and delineated three distinct profiles. In the first profile, a family solidarity was present between the parents and the kinship caregivers before the placement and was maintained during the placement. In the second, the parents struggled to keep their place in their children’s lives, thus experiencing conflicts both with the kinship caregivers and with the child-protection agency. In the third profile, the dynamics of the current relationship between both biological parents influenced the other family relationships of the parent who was interviewed.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.010 | 0.019 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".