Bosque mediterráneo: el corazón verde
Bibliographic record
Abstract
Self-forgiveness is generally understood to be a mechanism that restores and improves the self. In the current study, we examine the possible deleterious consequences of forgiving the self among gamblers-specifically in regard to gamblers' readiness to change their problematic behavior. At a large Canadian university, 110 young adult gamblers' level of gambling pathology was assessed, along with their readiness to change and self-forgiveness for their gambling. Participants were 33 females and 75 males (2 unspecified) with a mean age of 20.33. Results revealed that level of pathology (at risk vs. problem gamblers) significantly predicted increased readiness to change. Self-forgiveness mediated this relationship, such that level of gambling pathology increased readiness to change to the extent that participants were relatively unforgiving of their gambling. Implications for seeking professional assistance as well as treatment and recovery are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".