Educators of young children and knowledge of trauma-informed practice
Bibliographic record
Abstract
Decades of research on the impact of trauma in early childhood suggest severe risks to the mental health, emotional, social, and physical development of a young child. More recent research suggests that prolonged exposure to trauma can also affect a child’s ability to learn and their early academic success. Trauma-exposed students can pose a variety of different levels of challenges to schools and educators of young children and to date, few studies have addressed ECE teachers’ role in providing trauma support. An aim of the present study was to contribute to this literature by exploring the beliefs of BC early childhood education (ECE) teachers in their level of readiness and capability to work within a trauma-informed practice (TIP) framework to support their trauma-exposed students. Through a sequential, mix-methods approach, a self-report survey and semi-structured interviews were used to gauge BC ECE teachers’ knowledge of TIP, their preparedness, and their ability in using this framework to support their most vulnerable students. Teacher participants were recruited through the Early Childhood Educators of British Columbia conference and ECE community social media groups, Survey data was primarily collected through an online survey with interviews taking place in-person and audio-recorded. Survey results revealed that the majority of teachers believe they are somewhat prepared and able to apply the tenants of TIP in their classrooms despite a lack of training and resources provided by their schools and administrations. In follow-up interviews 14 subthemes emerged from a thematic analysis of the data under four broad themes: Challenges for ECE Teachers, Administrative Protocol and Support, Effective Approaches and Additional Support Desired by ECE Teachers. Findings of this study suggest ECE teachers are very interested in receiving more knowledge and training to provide optimal support for their trauma-exposed students.
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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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".