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Record W2780554855 · doi:10.5430/ijhe.v6n6p149

Forgiveness and Subjective Happiness of University Students

2017· article· en· W2780554855 on OpenAlexvenueno aff
Meryem Vural Batık, Tuğba BİNGÖL, Aynur Fırıncı Kodaz, Rumeysa Hoşoğlu

Bibliographic record

VenueInternational Journal of Higher Education · 2017
Typearticle
Languageen
FieldPsychology
TopicForgiveness and Related Behaviors
Canadian institutionsnot available
Fundersnot available
KeywordsForgivenessHappinessPsychologyResidenceSocial psychologyScale (ratio)Subjective well-beingClinical psychologyDemographySociology

Abstract

fetched live from OpenAlex

This research was conducted to investigate the forgiveness and subjective happiness level of university students in terms of gender, faculty, grade, residence, and parental attitudes, and to determine predictive role of forgiveness on subjective happiness. The study group consists of 828 university students (56.3% female, 43.7% male). The data was collected through the Forgiveness Scale and the Subjective Happiness Scale. The results of the study indicated that the level of forgiveness and subjective happiness of university students did not differ significantly in terms of gender and residence. On the other hand, it was found that the forgiveness level of third and fourth grade students and students who enrolled in Faculty of Theology were significantly higher than the other students. Moreover, the students whose parents are protective and democratic attitudes reported significantly higher levels of forgiveness and subjective happiness. There is a positive relationship but low between forgiveness and subjective happiness and; forgiveness was found as a significant predictor of subjective happiness.

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)0.000
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 score0.029
Threshold uncertainty score0.278

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.019
GPT teacher head0.380
Teacher spread0.362 · 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

Citations24
Published2017
Admission routes1
Has abstractyes

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