Bibliographic record
Abstract
Today, performance measurements have become a part of the dominant discourse across public, private, and voluntary sectors. Ontario’s child welfare system is one sector that has been influenced and impacted, with sometimes unintended consequences, by this institutionalized process of performance measurements. One of the measurements is Ontario’s Crown Ward Review (Audit) conducted by the Ministry of Children and Youth Services. Annually, ministry officials who make up the Crown Ward Review Unit (CWRU) audit fifty-three child welfare agencies in Ontario, which take care of approximately 5400 Crown Wards (Ministry of Children and Youth Services, 2011). According to the Ministry of Children and Youth Services (2011), the goal of the Crown Ward Review is “to determine that an adequate plan of care [has been] developed for each Crown Ward and is intended to stimulate improvement in the overall service delivery to children” (Ministry of Children and Youth Services, 2011). It appears to not only be about the welfare for Crown Wards, but also about organizational goals. In other words, measuring accountability, effectiveness, and efficiency, as well as to provide transparency of its services appears to be a priority. This research project examines how the performance measurements of the Crown Ward Review have impacted case management for Crown Ward workers and Crown Wards in care. A critical analysis of performance measurements reveals that, for the most part, they have created numerous unintended consequences for Crown Wards, workers, supervisors, managers, Children’s Aid Societies, and the child welfare system as a whole. Overall, the study supports that a more comprehensive, clear, and coherent review process needs to be established and implemented across Ontario’s child welfare system.
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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 | 0.141 | 0.363 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.024 | 0.024 |
| Science and technology studies | 0.035 | 0.014 |
| Scholarly communication | 0.018 | 0.004 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.006 | 0.007 |
| 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 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".