Exploring children's services workers’ perceptions of COVID-19: Trauma, connection and creativity
Bibliographic record
Abstract
• Participatory action research employing focus groups and interviews with 31 children's services workers in Western Canada revealed traumatic experiences and commitment and creativity in their work during the COVID-19 pandemic. • The COVID-19 pandemic created restrictions, inconsistencies in policy implementation and practice, increased stressors and workloads, yet social workers were creative and innovative and went beyond the norm to care for and meet the needs of children and families. • Recommendations for training, practice, and policy are offered to ensure future needs of children's services workers and children and families are met during times of adversity. Children services workers (CSWs) in child welfare during the COVID-19 pandemic were tasked with providing services amidst various government mandates and restrictions causing a multitude of effects. To examine the lived experience of CSWs practice during COVID-19. 31 CSWs were recruited from a Western Province in Canada. This participatory action research utilized 7 focus groups and 4 interviews with frontline and supervisory CSWs. Braun and Clarke's (2006) thematic analysis approach and coding processes were employed. The findings revealed difficult and traumatic experiences, along with the commitment, creativity and innovation of the workers. Technology was a necessary resource and a barrier in service delivery. Three main themes and associated subthemes that emerged included 1) the trauma of COVID, with subthemes: influences on CSWs, and influences on children and families, 2) practice context matters , with subthemes the impacts on policy and service delivery, and accessibility and lack of resources, and 3) connection, creativity, and removal of perceived barriers, with subthemes, relationships matter, and innovative practices. The study highlighted how CSWs were affected during the pandemic by government restrictions, inconsistent practice and policy implementation, increased stressors, and workloads, and the experience of deaths. It was evident that CSWs were courageous, creative, and innovative, as well as hardworking, committed, and persevered in providing services to children and families. Recommendations for training, practice and policy are offered.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.024 | 0.021 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".