I Can But You Can't: Inconsistencies in Judgments of and Experiences With Infidelity
Bibliographic record
Abstract
Despite strong prohibition against infidelity and endorsement of exclusivity as a norm, many people report engaging in infidelity. The current study examined this paradox by employing a between-subject design using online surveys with 810 adults to assess actor-observer biases in the degree of permissiveness judging own versus partner's hypothetical behaviour, as well as hypocrisy in judgments of infidelity versus self-reported behaviour. Participants judged their own behaviour more permissively than their partner's, but only for emotional/affectionate and technology/online behaviours (not sexual/explicit or solitary behaviours). Many reported having engaged in behaviours that they judged to be infidelity, especially emotional/affectionate and technology/online infidelity behaviours. Sexual attitudes, age, and religion predicted inconsistencies in judgments of infidelity and self-reported behaviour (hypocrisy). This study has implications for educators and practitioners working with couples to improve communication and establish guidelines for appropriate and inappropriate behaviour.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".