Investigation of the Interactive Positive Processes of Couples with Different Characteristics: A Qualitative Study
Bibliographic record
Abstract
Interactive processes encompass all those aspects of interpersonal and intrapersonal processes that affect the communication loop of couples. This study aims to test positive interactive processes among couples with different personality traits. In order to collect data, twenty psychotherapists specializing in couples’ therapy and forty eight couples of different personality traits referred to counseling centers of Yazd city were selected (using purposeful sampling). Semi-structured interviews were conducted and the procedure continued up to data saturation. Additionally, books, articles and Internet sites were additionally used for data collection. The research method of qualitative content analysis was conducted. positive test results obtained from the interactive processes between couples with different personality traits can be categorized into the open-ended codes of (levels of give and take, emotional control, Improve cognition, cognitive processing control, Efficient behaviors, planning, accountability, financial management and household) along with the four major codes of “cognitive, emotional, behavioral, and managerial” skills. Differences in personality traits can be traced to all mental, behavioral and functional dimensions of couples and can also influence the total level of communication between the couples. Therefore, taking these differences into account and learning how to manage them can reduce conflicts over such differences.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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 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".