Glossary of terms: A shared understanding of the common terms used to describe psychological trauma
Bibliographic record
Abstract
The use of language for mental health and mental health conditions often differs among professionals from various disciplines, and many words used in professional contexts have different meanings for people who are not health professionals.In addition, many cultural factors shape how we think about mental health and mental health conditions including values, preferences, clinical experience, and research results.For example, in recent years, the word "injury" has been used more often by many people to describe some mental health conditions, replacing the term "disorder," which has important meaning for health professionals.On the one hand, the word "injury" helps to diminish stigma that can accompany the term "disorder."On the other hand, the word "disorder" has a deep meaning for health professionals that communicates important information about a person's condition, functional limitations, and optimum treatment.The current Glossary is intended to promote a shared understanding of many of the common terms that are used to describe mental health and mental health conditions arising in the context of exposure to potentially psychologically traumatizing events and stressors.The intent is part of an ongoing effort to bridge any gaps that may exist between health professionals and the diverse communities they serve.The current Glossary focuses on Posttraumatic Stress Disorder and closely related terms, but that should not be misinterpreted as indicating other mental health conditions that can be caused by exposure to one or more potentially psychologically traumatic events, such depression, anxiety, psychosis, substance related harms, and suicide, to name only a few, are less important.As the fields of mental health and mental health conditions are ever-changing; the current Glossary is a "living document" that will be revised over time to reflect new understandings.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.019 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.071 | 0.038 |
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".