Certain personalities more likely to apologize
Bibliographic record
Abstract
Listen to the story on Rivet Sorry for the interruption... But apologizing may rely on more than just being \the bigger person.\ In a recent study, Australian and Canadian researchers have found that certain personality types are more likely to apologize. New York Magazine says 139 adults, averaging about 31 years old, took a personality test along with a selected friend or partner who also rated their personality. So who's most likely to say sorry? People who had high scores in conscientiousness as well as honesty and humility were more likely to apologize frequently. This makes sense, honest people may own up to their wrongdoing more likely than those who aren't aware or are too self-centered. One finding surprised the researchers...more agreeable people -- defined as those able to control their temper and who're more likely to forgive -- were LESS likely to give quick apologies. Even researchers are unsure why this is...sorry to say, some more research may need to be done to uncover the true science behind our \sorrys\.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.598 | 0.007 |
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".