Bibliographic record
Abstract
Abstract Mental illnesses are very common; more than one-quarter of people will develop a mental illness during their lifetime. Mental illnesses are associated with substantial disability in work, relationships, and physical health, and have been clearly established as one of the leading causes of disability in the developing, as well as the industrialized world. Mental disorders are common in every service sector important to social workers, and affect outcomes in every service sector. Mental disorders are strongly associated with poverty worldwide, and are common and often unrecognized in the general health sector, child welfare, and criminal justice settings, among others. Basic information about mental health is thus important to all social workers. Information about classification systems and major categories of mental illnesses, including depression, anxiety, psychotic disorders, and substance abuse disorders, is presented. The service system for mental disorders is badly underdeveloped, and most people who need treatment do not receive it. There is an increasing body of evidence demonstrating effective treatments, and policy is moving toward requiring that treatments offered be evidence based. This is a period of a great explosion of knowledge about mental health, and we can expect considerable advances in the coming years.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 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; 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".