Working with Child Victims During the COVID-19 Pandemic: A Qualitative Study of Child Maltreatment Investigators’ Experiences
Bibliographic record
Abstract
The present study adds to the growing body of knowledge on the impact of the COVID-19 pandemic by examining the experiences of Canadian child maltreatment investigators. Three focus groups were conducted with child maltreatment investigators (n = 16) from across Canada to investigate the impact of COVID-19 on child maltreatment investigators and the children and families they work with. Findings from this qualitative study relate to the personal and professional impact of COVID-19 on child maltreatment investigators and the impact of COVID-19 on investigators’ work practices. Subthemes relating to the impact of COVID-19 on child maltreatment investigators include fatigue, stress, and burnout; self-care and isolation; working from home with increasing workloads; child maltreatment investigators as essential workers; and workplace support. Participants’ work practices were impacted by rates of reporting throughout the pandemic, reduced in-person contact with clients, remote services and communication, and COVID-related safety protocols and challenges. Recommendations stemming from these focus groups include the recognition of child maltreatment investigators as essential workers, access to adequate counseling services for child maltreatment investigators, workplace flexibility for child maltreatment investigators, and ensuring that child protection agencies are adequately resourced to maintain manageable workloads.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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, unvalidatedMachine predicted; a candidate call from one teacher head, 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".