Constructing professional boundaries: external experts’ perspectives on their role and function in care proceedings in Norway
Bibliographic record
Abstract
This article explores how external experts in Norway perceive their role and function when commissioned to assist Child Welfare Service (CWS) assessments in care proceedings. Based on qualitative interviews with twelve external experts, we specifically examine how these experts draw professional boundaries towards social workers when commissioned to assess child welfare cases and how these boundaries are legitimized. Our analysis found that the experts constructed these professional boundaries by positioning themselves along two dimensions: One, relating to horizontal boundaries, emphasizing their external position in the child welfare system. Another dimension was related to vertical boundaries, pointing to their additional analytical qualifications that social workers lack. However, some described cases where the role and contribution of external experts were redundant and the professional boundaries became blurred. The findings address the need to discuss what constitutes valid knowledge in a care assessment and how boundary work between external experts and child welfare social workers can contribute to the quality of care assessments in child protection cases.
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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 | 0.040 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.020 | 0.033 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".