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. As trauma-exposed students can pose a variety of different levels of challenges to schools it is essential address the importance of trauma-informed classrooms and schools. This poster presentation aims to contribute to the literature in support of the implementation of Trauma-Informed Practice (TIP) in educational settings as well as provide an outline of the required elements of an effective trauma-informed System. Drawing from the available literature, this presentation hopes to highlight the necessity of a concrete, holistic approach to the creation of trauma-informed schools that is well thought out, research-based and implemented at every necessary level of the school system.
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
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 | 0.014 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.023 | 0.021 |
| Scholarly communication | 0.026 | 0.038 |
| Open science | 0.004 | 0.033 |
| Research integrity | 0.016 | 0.021 |
| Insufficient payload (model declined to judge) | 0.031 | 0.010 |
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".