But the wheels are square! Synchronizing outcome-based and relational practice
Bibliographic record
Abstract
The perennial tension between the social work aspiration to engage in their clients' lives and the ever growing administrative requirements of their jobs is growing, accompanied by increased risk avoidance fuelled by public crises of confidence in child welfare. The net effect on service providers has been a massive growth in procedural work and data gathering in a vain attempt to prevent the next tragedy that will inexorably lead to even more of the same. This has substantially reduced the time available for child welfare caseworkers to fully engage with the families and communities they serve. Results based management, or in Alberta Outcome Based Service Delivery (OBSD), asks caseworkers to more fully engage with the families and communities they serve. Early experiences from the U.K. tell some cautionary tales about relational objectives taking second place to the administrative work of outcome delineation, and management having to manipulate the statistical outcome data as caseworkers fail to keep up. The province of Alberta in Canada is currently implementing OBSD. This paper raises concerns about the direction taken and some ideas on how to ensure quality partnerships with families and communities that are not overwhelmed by increased paperwork, the curse of child welfare work for the past 30 years.
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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 | 0.064 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.031 |
| Scholarly communication | 0.020 | 0.036 |
| Open science | 0.003 | 0.024 |
| Research integrity | 0.006 | 0.016 |
| Insufficient payload (model declined to judge) | 0.018 | 0.006 |
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".