How has child maltreatment surveillance data been used in Canada?
Bibliographic record
Abstract
BACKGROUND: Recently, a survey was performed as part of a larger study at the Public Health Agency of Canada (PHAC) to develop and pilot a series of tools to measure the uptake and use of PHAC-produced or -supported knowledge products by its key partners and stakeholders. This article aims to i) examine the uptake and use of the Canadian Incidence Study of Reported Child Abuse and Neglect 2008 (CIS-2008) and to ii) assess the utility of a knowledge uptake survey for collecting performance measurement data. METHODS: Using the knowledge utilization ladder as a theoretical framework, a short survey was developed around the themes of reception, cognition, conversation, reference, effort, influence, and implementation. The survey was administered electronically to potential end-users of the CIS-2008. The final sample comprised 85 respondents. RESULTS: The results demonstrated that the majority of the respondents were aware of CIS-2008 and had read and used it. A wide array of disciplines and sectors were identified as end-users. Types of use included discussion of CIS data with social workers, child welfare and health advocates, students, medical and legal professionals, and senior government decision makers. Further, CIS was referenced in reports, articles, policy research, community programs, and funding proposals and was used to influence or support the development of policies, programs, and projects. Valuable information on the use of surveillance reports, such as CIS-2008, can be gathered from a brief survey that was easy to administer, cost effective, and that respondents needed minimal time to complete. CONCLUSIONS: Piloting of the survey demonstrated that the tool, while not perfect, is quite useful for capturing performance measurement information; CIS-2008 is appreciated and used. There is an increased recognition of the importance of the CIS as a unique source of Canadian child maltreatment surveillance data that can influence and lead to the implementation of new programs and policies. Although suggestions for improvement of the CIS-2008 were provided, the present findings offer support for ongoing national child maltreatment surveillance.
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.
How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | medium |
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
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".