Suicide, Big Five Personality Factors, and Depression at the American State Level
Bibliographic record
Abstract
The research determined the relation of the 2004–2005 American state suicide rates to state means on neuroticism, agreeableness, extraversion, openness, and conscientiousness as assessed by Rentfrow, Gosling, and Potter (2008 Rentfrow , P. J. , Gosling , S. D. , & Potter , J. ( 2008 ). A theory of the emergence, persistence, and expression of geographic variation in psychological characteristics . Perspectives on Psychological Science , 3 , 339 – 386 .[Crossref], [Web of Science ®] , [Google Scholar]). Multiple regression strategies were used to analyze relations between state suicide rates and state personality means with state socioeconomic status, White population percent, urban population percent, and depression rates controlled. Multiple regression analysis showed that neuroticism accounted for 32.0% and agreeableness another 16.3% of the variance in suicide rates when demographics and depression were controlled. Lower neuroticism and lower agreeableness were associated with higher suicide rates. Lower neuroticism and lower agreeableness may be important risk factors for completed suicide but not suicidal ideation or attempted suicide.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".