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Record W7108079914 · doi:10.17605/osf.io/g5a3c

FROM WORDS TO FOOD - A CROSS-CULTURAL STUDY OF PARENTAL APOLOGIES AND FORGIVENESS

2025· other· W7108079914 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Science Framework · 2025
Typeother
Language
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsForgivenessNonverbal communicationInterpersonal interactionInterpersonal communicationSelf-disclosureInterpersonal relationshipAsian culture

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.009
Science and technology studies0.0020.010
Scholarly communication0.0100.003
Open science0.0170.023
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.054
GPT teacher head0.421
Teacher spread0.367 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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Same venueOpen Science FrameworkFrench-language works237,207