The four dimensions: a model for the social aetiology of psychosis
Bibliographic record
Abstract
Recently, there has been increasing focus on prevention of mental illness, early intervention and the promotion of mental health. The social determinants of health and public health approaches are considered key. Early intervention has focused on psychotic disorders but prevention has not. This may in part reflect the fact that public health planners do not have a clear model for how social determinants influence the risk of developing a psychotic illness. Drawing on biological, genetic and epidemiologic evidence regarding the relationship between social risk factors and psychosis, this paper outlines a conceptual framework for understanding how individual and ecological factors contribute and interact to modulate the risk of developing psychotic illness. The framework asserts that there are four dimensions: individual factors; ecological factors; the interaction between individual and ecological factors; and time. It may help those considering interventions to understand the multilevel and multifactorial effects of social factors on the aetiology of psychotic illness, to develop targeted strategies for the prevention of psychotic illness and serve as a template for the assessment of initiatives.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".