Interdisciplinary approaches to understand traumatic stress as a public health problem
Bibliographic record
Abstract
In November 2016 researchers, clinicians, and student experts gathered in Dallas, Texas, USA for the annual meeting of the International Society for Traumatic Stress Studies (ISTSS). From the description of the meeting theme forward it was acknowledged that interdisciplinary approaches will be required to fully understand traumatic stress as a public health problem, including epidemiology, biostatistics and health services research. Further, it was recognized that knowledge translation would be of critical importance if we were to increase public awareness of - and destigmatize - posttraumatic biopsychosocial problems, including posttraumatic stress disorder (PTSD). Moreover, we recognized innovative technologies as potentially usefully applied to public health strategies, including media and internet usage might aid knowledge translation and have a direct impact on help-seeking and trauma-informed care. The present special issue of the journal brings a collection of papers from some of the most impactful and innovative ideas that were presented in Dallas.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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; both teacher heads agree on what is shown here.
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".