Protect the individual or protect the relationship? A dual-focus model of indirect risk exposure, trust, and caution
Bibliographic record
Abstract
The current study extends work by both Boon and Holmes (1999) and Murray, Holmes and Collins (2006) by providing a theoretical model and the first experimental examination of the connection between more subtle forms of risk exposure and the levels of trust third-party evaluators have in their own partners when giving advice to others about their relationship difficulties. One hundred and fifty-two participants initially completed trust and self-esteem scales. They returned to the laboratory one week later and read either a narrative designed to prime the risks inherent in romantic relationships or a control narrative. All participants then read and evaluated an account of events that occurred in someone else’s romantic relationship and gave advice to the victim. The results of our study suggest that indirect risk exposure and trust, in combination, do significantly predict initial evaluations of the event, the attribution of responsibility and blame, focus of caution, and advice to the victim. The only exception to this pattern was the absence of an interaction between risk and trust on our measures of suspicion and desire for further information. A dual-focus model of indirect risk exposure, trust, and caution is proposed.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".