Investigating Marital Infidelity from the Perspective of Payame Noor and Azad Universities’ Students in Bileh Savar County in 2015
Bibliographic record
Abstract
Infidelity is one of the problems which families are involved in and it goes forward to complete separation. Of course, this problem existed long time ago, with this difference that infidelity and polygamy were common categories in families in the past and they were a privilege especially for men. Sometimes, even women themselves were looking for a wife for their husband. However, at the present time, polygamy is not considered as a privilege and value and even women are not willing to share their husband with another woman. This subject has become a problem in families. The research population consisted of students (male and female) of Payame Noor and Azad Universities in Bileh Savar County. All students of Payame Noor University were 500 and students of Azad University were 1000. Since there were no accurate statistics of married students at both universities, and also due to the lack of financial ability and high costs of research analysis, 150 students were randomly selected as the sample of research. Survey research method and questionnaire were used for data collection. Statistical methods were applied in the forms of descriptive statistics (frequency table, percent, charts) and referential statistics (Pearson test, t-test).
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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 | 0.001 | 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 | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".