The Relation Among Self-Esteem Caping Skills and Occuational Performance in Battered Women
Bibliographic record
Abstract
Purpose: This study was conducted to examine the correlation between self-esteem, coping skills and occupational performance in battered women. Materials and Method: 10 battered women at the ages of 18 or above, who were staying at Sheltered Home of Çankaya Municipality, volunteered to take part and were included in the study. Information on women’s socio-demographic and violence was recorded. For the assessment of self-esteem Rosenberg Self-Esteem Scale (RSE) and coping skills Coping Styles Inventory (SCI) were used. Canada Occupational Performance Measurement (COPM) was used to identify the occupations and occupational performance that people find important in their lives. Results: A correlation between self-esteem, coping skills and occupational performance was not found. However, a significant correlation between occupational satisfaction and coping skills was found. Conclusion: The occupational satisfaction of battered women who develop coping skills was higher than the ones who do not develop them. It was thought that occupational satisfaction of battered women can be increased by increasing their coping skills. Considering the occupational satisfaction has a dynamic relationship with the occupational performance, it was thought that performance can be enhanced. Moreover, it was seen that women have occupational performance problems, which suggested that future studies that interfere in this matter should be made.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".