Using Web-Based Technologies to Increase Evaluation Capacity in Organizations Providing Child and Youth Mental Health Services
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
Abstract: Given today’s climate of economic uncertainty and fiscal restraint, organizations providing child and youth mental health services are required to do so with limited resources. Within this context, service providers face added pressure to deliver evidence-based programs and demonstrate program effectiveness. The Ontario Centre of Excellence for Child and Youth Mental Health works with organizations to meet these demands by building capacity in program evaluation. While personal instruction and mentoring are important ways of providing support, face-to-face consultations are not always cost-effective. In this article we describe the use of interactive technology and computer-based learning as an alternative and/or complementary (to face-to-face) means of delivering evaluation information and training. We discuss the process of developing these tools and share findings from our preliminary evaluation of their effectiveness in enhancing the evaluation-related supports we offer to providers of child and youth mental health services.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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