A cybernetic framework linking personality and other variables in understanding general health
Bibliographic record
Abstract
Personality traits such as anxiety, self‐esteem and aggressive hostility are often thought to affect the stress that a person perceives or manifests. With data from 176 male executives, this study suggests that there are indirect and interacting relationships between personality and general health. This article proposes a cybernetic framework that links personality with other variables in understanding overall health. The framework specifies that personal characteristics (i.e. age), personality, and environment all play a role, each interacting systemically. The framework provides a basis for illustrating these interactions. For example, while type A personalities are more likely to get involved in more stressful situations, their negative health effects might depend on other variables, such as self‐esteem and years in the job. While personality features are important risk factors, they may not, by themselves, predict stress. Stress is the result of interacting variables including age, position, job level, the stress experience, and one's personality.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".