Decision-making in foster care: A view on the dynamic and collective nature of the process
Bibliographic record
Abstract
Summary Placement in a foster family by child welfare services is a crucial decision in the trajectory of a child. Nevertheless, the strategies and procedures underlying the decision to remove a child from his/her family for placement in foster care remain little studied. Based on 39 semi-directed individual interviews with social workers from child welfare services, the current study aims at highlighting how social workers come to the decision to remove a child from parental care, and how they choose a foster family. Findings The thematic analysis of the qualitative data collected reveals that four main components were raised by social workers to explain how they make their decisions regarding placement and what are the considerations associated with this process: (1) Professional consensus and collaboration, (2) Clinical and legal guidelines, (3) Risk assessment and clinical judgment, and (4) Personality and values of the social worker. The results of this study show that decisions surrounding the removal of a child from his/her family and the choice of a foster family are the result of multiples factors and strategies involving the social worker and other collaborating professionals, as well as their legal and administrative context. Application The findings suggest that additional efforts could be made in child protection organizations and agencies in order to develop supportive measures that take into account the collective and interactional aspect of the decision-making process regarding placement in foster care.
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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 | 0.024 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.035 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| 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".