Child Protection Decision Making: A Factorial Analysis Using Case Vignettes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study explored decision making by child protection social workers in the province of British Columbia, Canada. A factorial survey method was used in which case vignettes were constructed by randomly assigning a number of key characteristics associated with decision making in child protection. Child protection social workers (n = 118) assessed case vignettes (n = 327) for risk, service provision, and importance of client contact. In British Columbia, child protection social workers are expected to make decisions using a risk assessment model. However, as social workers begin to work with clients to facilitate change, relationship factors such as home visits and client contact also become important. The research indicated that social workers made decisions through an integration of objective, procedural, and experiential knowledge. Decisions about risk and service provision were influenced by technocratic knowledge, such as the risk assessment model. Decisions related to the amount of contact with clients and other supportive functions were influenced by individual characteristics of the social workers. The results suggest that in child protection decision making, social workers are moving beyond a reliance on objective tools such as risk assessment to also use internalized subjective knowledge.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it