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Record W3161480672 · doi:10.31234/osf.io/q9r72

Forgiveness at Work, Forgiveness at Home? Testing the Context-Dependence of Forgiveness-Related Attitudes and Values

2021· preprint· en· W3161480672 on OpenAlexaff
Lukas Neville

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicForgiveness and Related Behaviors
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsForgivenessContext (archaeology)Social psychologyPsychologyWork (physics)Perception

Abstract

fetched live from OpenAlex

Research and theory on forgiveness in the workplace draws considerably on results from the study of close relationships. This paper considers whether forgiveness-related attitudes and perceptions systematically differ in the home versus workplace contexts. Previous work suggests that people may see forgiveness as less appropriate to express at work than at home, and that they may adjust their values or attitudes relating to forgiveness depending on whether the transgression is personal or professional. It is important to understand whether context shapes forgiveness, because it speaks to the appropriateness of generalizing from theory and research in close relationships when studying forgiveness in organizations. Across three studies (n=944), we experimentally manipulate context (work versus home), and test its effect on forgiveness, the forgivingness of self and others, attitudes toward forgiveness, the perceived riskiness of forgiveness, the willingness to forgive unconditionally, sources of forgiveness aversion, and reactions to others’ forgiveness. In each case, we find no evidence to suggest that forgiveness-related attitudes differ substantively between the home and workplace contexts. We conclude by discussing the implications of this finding for forgiveness as an interdisciplinary topic of study.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.049
GPT teacher head0.317
Teacher spread0.268 · 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; a candidate call from one teacher head, not a consensus.

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

Citations1
Published2021
Admission routes1
Has abstractyes

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