Bibliographic record
Abstract
Evaluative research in the field of mental health is carried out pursuant to several goals. One is to study a very particular intervention on a very particular client (or client population) in a controlled way with the aim to test a theory of intervention. This form of research requires basically an experimental research design. It also requires rigorously defined and measured intervention and a good control for factors other than intervention. The requirements for this form of research are stringent and the number of such projects reported is, therefore, rare. The present study was done as a pilot study for the Elahan Center for Mental Health and Family Living (formerly Clark County Mental Health) in Vancouver, Washington. This agency has recently undergone much change. About eighteen months ago there was a change of Directors. At about the same time, though unrelated, the agency was involved in a public scandal around the drug program. As a result of much inter-agency strife and the change in administration, few employes from the old staff remain. The new administration is dedicatedly behaviorist in therapeutic orientation, as are some of the therapists. Use of para-professionals in professional capacities is high and most of tile para-professionals follow the behavioristic bent of the administration.
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 | 0.013 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".