Bibliographic record
Abstract
The Canadian Red Cross approved funding for the Psychologists’ Association of Alberta through its Alberta Wildfires 2016 Community Organization Partnership Program. Funding was used to directly resource psychological trauma assessment and treatment until June 2020. Outcome-informed practices were employed to empirically validate treatment employing the Outcome Rating Scale (ORS). Sixteen approved psychologists provided trauma-informed services to 349 clients over 3 years, with the ORS being completed at five-session intervals. Results indicated very low levels of functioning and well-being at intake. For adults, overall average functioning and well-being increased over the treatment period. By the 5th, 10th, and 15th sessions, there was an average reported increase in perceived well-being of 65%, 57%, and 100%, respectively. Treatment made a significant difference for clients. The resulting five primary recommendations are 1) to provide timely access to qualified assessment and treatment, 2) to conduct trauma-informed screening of referrals, 3) to identify and provide additional resources for vulnerable populations, 4) to tailor services to gender considerations, and 5) to take steps to reduce barriers to accessing assessment and treatment.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.000 |
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".