Bibliographic record
Abstract
“Trauma-informed care” provides a framework to guide clinicians in responding to the epidemic of trauma. Yet few clinicians feel comfortable defining trauma-informed care or describing how it translates into practice. This reflective piece suggests four dimensions of trauma-informed care: 1) Awareness of the prevalence of trauma and its long-term effects on physical and emotional health to every encounter; 2) attitudes that recognize resilience and take into account how trauma may influence behavior and engagement in care; 3) an approach to care that prioritizes safety, choice and collaboration while working to build trust; and 4) education regarding trauma’s effects, and connection to resources to support healing. These dimensions seek to clarify the provider’s role in creating a trauma-informed health care environment and stimulate reflection on how best to serve patients affected by trauma.
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 | 0.031 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.035 |
| Scholarly communication | 0.016 | 0.017 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.012 | 0.039 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".