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Record W4400109924 · doi:10.1080/03057240.2024.2360210

Effectiveness of forgiveness education with adolescents in Iran: Increasing the positive psychology of empathy, altruism, and willingness to forgive

2024· article· en· W4400109924 on OpenAlexaboutno aff
Bagher Ghobari Bonab, Mohamad Khodayarifard, Ramin Hashemi Geshnigani, Behnaz Khoei, Fatimah Nosrati, Jacqueline Y. Song, Robert D. Enright

Bibliographic record

VenueJournal of Moral Education · 2024
Typearticle
Languageen
FieldPsychology
TopicForgiveness and Related Behaviors
Canadian institutionsnot available
Fundersnot available
KeywordsForgivenessEmpathyAltruism (biology)PsychologySocial psychologyProsocial behavior

Abstract

fetched live from OpenAlex

The aim of the current study was to investigate the effect of forgiveness education on positive psychology variables (empathy, altruism and willingness to forgive) in Iranian adolescents. Two hundred twenty-four (Persian, Azeri, and Kurdish) male and female students in eighth grade participated. Schools were randomly assigned to experimental (N=123) and control (N=101) groups. Measures include the Toronto Empathy Questionnaire, Altruistic Personality Scale, and Willingness to Forgive Scale, administered at pre-test, post-test, and follow-up. The experimental group was presented with 15 weekly sessions of teaching forgiveness programs by classroom teachers. The results showed that the experimental group improved more in degrees of empathy, altruism, and willingness to forgive compared to the control group, and also at follow-up. It seems that forgiveness education programs can contribute to human flourishing with the increase of positive psychology in students, particularly in empathy, altruism, and willingness to forgive.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.015
GPT teacher head0.356
Teacher spread0.341 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2024
Admission routes1
Has abstractyes

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