Bibliographic record
Abstract
The ways in which personality and health interact are myriad and complex. Does personality predispose us to certain diseases? Does disease lead to changes in personality? The original formulation of psychosomatic medicine sought a direct link between personality and health – anxiety and hypertension, depression and cancer – and was largely unfruitful. Current research seeks to clarify how personality is associated with health-related behaviours like smoking and exercise, which put people at risk for disease. By elucidating the link between personality and health behaviours, the field makes substantive contributions to both patient treatment and public health prevention and intervention programmes aimed at reducing the incidence and prevalence of disease. Personality as traits For most of history, scholars and laypersons alike viewed human beings as rational creatures with propensities, abilities and beliefs that guided their conduct. Early in the twentieth century, this view was supplanted by psychoanalysis and behaviourism which characterized personality in radically different ways: for psychoanalysts, the essence of the person was in unconscious and often irrational processes; for behaviourists, the person was no more than a collection of learned responses to environmental reinforcements. Contemporary research has in turn rejected these two extreme views of personality and returned to a more commonsense approach, in which familiar traits such as persistence and sociability are seen as important determinants of behaviour. It does not follow, however, that personality psychology is nothing but common sense.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".