Trauma-informed practice: A self-study examining the readiness of pre-service early years professionals
Bibliographic record
Abstract
Childhood psychological trauma is currently gleaning attention in many fields of study. Subsequently, Trauma-Informed Practice (TIP) is becoming integral to many organizations that service children and families. A gap, however, is noted in literature between this approach to practice and pre-service early years professionals who study to work in care and education settings as either early childhood educators or teachers. Furthermore TIP, using Self-Study (SS) methodology, is deficient in literature. Thus, a Self-Study was enacted by four pre-service early years professionals, in their fourth and final year of their degree, to investigate their preparedness to employ TIP in their work post-graduation. A Critical Friend, versed in this topic, engaged in this study as this is habitual to SS methodology. Findings of this research convey that TIP is covertly addressed in course content, indicating that this area of pedagogy requires more explicit attention in pre-service curriculum. Outcomes of this study also illuminate the urgency for early years professionals to address their own adverse experiences so that they are situated to cultivate attuned and responsive trauma-informed climates in their pedagogical practice.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".