Comparison of Early Maladaptive Schemas, Lifestyle, Resilience and Happiness in Iranian Women Working in Toronto and Tehran with Emphasis on the Role of Immigration
Bibliographic record
Abstract
Introduction: One of the most important developments in immigration in recent decades is the increasing involvement of women in the immigration process and the increase in women's independent immigration, which is called the feminization of immigration. This study aimed to comparing Iranian women working in Toronto and Tehran in lifestyle, early maladaptive schemas, resilience, and happiness.Methods: The present study was a causal-comparative study. The statistical population included all Iranian women working in Tehran and Iranian women immigrating to – Toronto, Canada. Using the convenient sampling method, 89 Iranian women working in Toronto and 93 Iranian women working in Tehran were selected (Out of the total number of questionnaires, 11 questionnaires from the group of immigrants and 7 questionnaires from the group of non-immigrants were excluded due to being distorted). Data collection tool included Young Schemas Questionnaire (YSQ-SF), Adler Basic Scales for Interpersonal Success - Adult Edition (BASIS-A), Connor & Davidson Resilience Scale, and Happiness / Depression Inventory.Results: The results of MANOVA showed that there is a significant difference between the mean scores of some lifestyle components (p<0.05), a number of early maladaptive schemas (p<0.05), happiness components (p<0.05), and resilience of immigrant and non-immigrant women (p<0.05).Conclusion: Accordingly, immigration in Iranian women can be a factor for changes in various aspects of psychology such as resilience, happiness and lifestyle.
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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 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".