MétaCan
Menu
Back to cohort
Record W1731736729 · doi:10.1111/spc3.12119

Self‐forgiveness: The Good, the Bad, and the Ugly

2014· article· en· W1731736729 on OpenAlex
Michael J. A. Wohl, Kendra J. McLaughlin

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSocial and Personality Psychology Compass · 2014
Typearticle
Languageen
FieldPsychology
TopicForgiveness and Related Behaviors
Canadian institutionsCarleton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsForgivenessPsychologySocial psychologyWrongdoingFeelingPessimismSelfPresuppositionEpistemology

Abstract

fetched live from OpenAlex

Abstract Traditionally, self‐forgiveness has been framed as a process that helps facilitate psychological as well as physiological well‐being following wrongdoing. In the present paper, we outline the limits and boundaries of this presupposition. Specifically, we outline contexts in which self‐forgiveness might yield negative consequence that include, among other things, a continuation of the wrongful behavior. First, we provide evidence that self‐forgiveness for ongoing, wrongful behavior (e.g., smoking) alleviates negative feelings associated with acknowledged wrongs committed by the self, which does little to motivate behavioral change. We then discuss the complication that is pseudo‐self‐forgiveness – a situation in which people shift some responsible away from the self for wrongs committed by the self. This outward shift in responsibility lets the self “off the hook”, which increases the likelihood that the wrongful behavior will continue. Drawing on these discussions, a path model for behavioral change that places self‐forgiveness at its core is offered. Although we present some pessimism regarding the outcome of the self‐forgiveness process, this paper points to situations and attributions that maximize its positive effects.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.828
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
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 head0.028
GPT teacher head0.336
Teacher spread0.308 · 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