“It Could Be Better” Can Make It Worse: When and Why People Mistakenly Communicate Upward Counterfactual Information
Bibliographic record
Abstract
Imagine you are a real estate agent and are showing a prospective buyer a house with a lake view, but it is foggy, and the view is less than ideal. Are you inclined to tell the prospective buyer, “Unfortunately, it is foggy outside. If it were not foggy, the view would be even better!”? Eight studies, spanning diverse domains, reveal a novel discrepancy: most presenters (e.g., the seller) choose to communicate such upward counterfactual information (UCI) to experiencers (e.g., the prospective buyer), believing it will enhance experiencers’ impressions (e.g., of the house)—yet UCI actually worsens their impressions. This discrepancy arises because presenters insufficiently account for the fact that they possess more knowledge about the presented target than experiencers do; they fail to realize that noting an imperfection reveals it. Accordingly, when experiencers are knowledgeable about the target, either because the imperfection is obvious or because they can easily envision the upward counterfactual, the discrepancy attenuates. Finally, the presenter–experiencer discrepancy occurs only when the counterfactual information is upward, such that presenters do not overcommunicate downward counterfactual information, which rules out a desire to share any information as an alternative mechanism for presenters’ communication decisions. Together, this research highlights the prevalence and costs of sharing UCI.
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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 | 0.084 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".