Parents’ and child welfare workers’ understandings of consent to emergency placements
Bibliographic record
Abstract
Emergency placements of children are often made in haste and experienced as dramatic. This article is based on interviews with 9 parents who have consented to emergency placements and their caseworkers. We explore parents’ reasons for giving their consent to placement and the child welfare workers’ understanding of these consents. This leads to a discussion of what constitutes valid consent from parents in emergency cases. Relational autonomy is applied as a perspective to understand the context and influencing factors of parental consent. The results, derived by thematic analysis, show three main themes regarding parents’ reasons for their consent: (1) The child wanted to move out, (2) the parents couldn’t manage the situation, and (3) parents felt the child welfare service (CWS) gave them no choice. Parents experience a high degree of pressure in the context of giving their consent, either from their child or the CWS. Asymmetrical power dynamics between the CWS and parents were highly present and relevant in parents’ reasons for consent, especially when the CWS communicated that the alternative to consent is coercive placement. Furthermore, it is often unclear to the parents what consent entails. This is especially evident through CWS’s regulation of child-parent contact. In the discussion, we emphasize a high degree of awareness on the part of CW workers with regards to understanding how contextual and relational factors influence parent’s choice to consent; when consent is valid; how far consent extends, and the potential weakening of parents’ legal security when a voluntary placement is conducted.
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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 | 0.021 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| 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".