FROM WORDS TO FOOD - A CROSS-CULTURAL STUDY OF PARENTAL APOLOGIES AND FORGIVENESS
Bibliographic record
Abstract
In the present research, we examined if and how Chinese and Canadian parents apologize to their children after a wrongdoing, focusing on verbal vs. nonverbal apologies. In Study 1, we investigated university students who reported their parents' apology tendencies, whereas in study 2, parents reported their own apology tendencies. We expected that Canadian parents are more likely to give verbal apologies than Chinese parents, and Chinese parents are more likely to give nonverbal apologies than Canadian parents. We explored the relational and emotional consequences of giving and receiving verbal vs. non-verbal apologies, such as forgiveness and change in closeness. We also explored the potential mechanisms of the expected cultural differences including filial piety, perceived effectiveness of apologies, and relationship quality.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.009 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.017 | 0.023 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".