The Relative State Model: Integrating Need-Based and Ability-Based Pathways to Risk-Taking
Bibliographic record
Abstract
Who takes risks, and why? Does risk-taking in one context predict risk-taking in other contexts? We seek to address these questions by considering two non-independent pathways to risk: need-based and ability-based. The need-based pathway suggests that risk-taking is a product of competitive disadvantage consistent with risk-sensitivity theory. The ability-based pathway suggests that people engage in risk-taking when they possess abilities or traits that increase the probability of successful risk-taking, the expected value of the risky behavior itself, and/or have signaling value. We provide a conceptual model of decision-making under risk-the relative state model-that integrates both pathways and explicates how situational and embodied factors influence the estimated costs and benefits of risk-taking in different contexts. This model may help to reconcile long-standing disagreements and issues regarding the etiology of risk-taking, such as the domain-generality versus domain-specificity of risk or differential engagement in antisocial and non-antisocial risk-taking.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".