Validation of the compassionate engagement and action scales, compassion scale, and Sussex-Oxford compassion scales in a French-Canadian sample
Bibliographic record
Abstract
Compassion towards oneself and towards others has been associated with positive psychological outcomes, however, research is limited by the availability of valid psychometric measures, particularly in languages other than English. The current study translated (English to French) and validated the following measures: the Compassionate Engagement and Action Scales (CEAS), assessing self-compassion (CEAS-SC), compassion to others (CEAS-TO), and compassion from others (CEAS-FROM); the Compassion Scale (CS); and the Sussex-Oxford Compassion Scales for Self (SOCS-S) and Others (SOCS-O). French-speaking participants were recruited online (N = 384) and completed the translated measures as well as questionnaires assessing self-compassion, depression, anxiety, stress, insecure attachment, mindfulness, and well-being. Confirmatory Factor Analysis supports the original factor structures proposed for the CEAS-FROM (two-factor hierarchical), CS (four-factor hierarchical), SOCS-S and SOCS-O (five-factor hierarchical), with alternate factor structures proposed for CEAS-SC (three-factor) and CEAS-TO (two-factor). Results showed good internal consistency and convergent validity for all scales, supporting the use of total scores for the translated measures.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".