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Record W2146920901 · doi:10.1521/jscp.2013.32.10.1095

Forgiveness and Revenge: The Conflicting Needs of Dependents and Self-Critics in Relationships

2013· article· en· W2146920901 on OpenAlexaff
Rebecca Young, C. Ward Struthers, Careen Khoury, Saara Muscat, Curtis E. Phills, Myriam Mongrain

Bibliographic record

VenueJournal of Social and Clinical Psychology · 2013
Typearticle
Languageen
FieldPsychology
TopicForgiveness and Related Behaviors
Canadian institutionsYork University
Fundersnot available
KeywordsPsychologyForgivenessSelf-criticismSocial psychologyContext (archaeology)PersonalityDependency (UML)Interpersonal relationshipCriticismInterpersonal communicationDevelopmental psychology

Abstract

fetched live from OpenAlex

The ability to forgive in the face of conflict is an important part of maintaining relationships, particularly for individuals with dependent and self-critical personality styles who can become depressed in response to interpersonal stress. This research examined the forgiveness process in relation to these personality styles in two separate studies. Study 1 was a nonexperimental retrospective study in a community sample of adults. Study 2 was an experimental study involving the manipulation of a transgression and relationship threat within the laboratory. The results of both studies confirmed a predicted 3-way interaction between self-criticism, dependency, and relationship threat on forgiveness and revenge. Specifically, self-critics who were low in dependency were more vengeful and less forgiving when their relationship was threatened. However, self critics who were also higher in dependency were more forgiving and less vengeful after experiencing a relationship threatening transgression. Results showed that self-critics were buffered from their typical harsh post transgression reactions if they were also higher in dependency. This research illustrates the importance of examining the interaction between self-criticism and dependency in the context of interpersonal functioning.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.121
GPT teacher head0.469
Teacher spread0.349 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2013
Admission routes1
Has abstractyes

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