Correlates of Divine Forgiveness in South Africa: National Survey
Bibliographic record
Abstract
A professional survey company undertook a cross-sectional national survey amongst a representative sample of black (African), coloured, white, and Indian South African (SA) adults drawn from the general population. Prior research (but not in South Africa, SA) has identified key constructs known (or predicted) to correlate (positively or negatively) with experiencing Divine Forgiveness (DF). The broad aims of the study are to: (1) replicate prior findings of correlates of DF (e.g., religiosity, empathy); (2) identify additional constructs that should be measured when researching DF in SA; (3) investigate relations between DF and different types of forgiveness (especially, intergroup forgiveness, IGF, including items about both racial ingroup and outgroup members’ transgressions, during the apartheid era), controlling for known correlates of each; (4) investigate the costs and benefits of DF; and (5) conduct Surplus Value Tests (SVTs) of DF for both interpersonal forgiveness (IPF) and intergroup forgiveness (IGF).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".