Personality Types and Patterns of Marital Conflict among Married Staff of Selected Universities in Southwest Nigeria
Bibliographic record
Abstract
This study investigated the personality types and patterns of marital conflict among the staff of universities in southwest Nigeria. The study adopted a descriptive survey design. 1330 married staff members, proportionately selected from nine universities, using a multi-stage sampling technique, constituted the study sample. Prevalence of Patterns of Marital Interaction Questionnaire (PPMIQ) and Personality Type Questionnaire (PTQ) were used to collect data for the study. The results showed that 67.1% of the staff indicated that they experienced demand-withdraw pattern, while 26.8% experienced constructive pattern. Only 6.1% experienced a destructive pattern. The results also showed that the largest percentage of the staff (20.3%) indicated that the possessed Introverted Intuitive personality while 16.9% and 16.8% demonstrated Extroverted Thinking and Extroverted Feeling personalities respectively. The smallest percentage (1.9%) demonstrated Introverted Sensational Personality. Also, from the result of this study, it is obvious that married staff in universities in southwest Nigeria have one form of marital conflict or the other. Furthermore, based on the results of the analysis, it could be concluded that all three patterns of marital conflict are being experienced by the married staff. The demand-withdraw pattern, however, appeared to be the typical pattern among the married staff.
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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 | 0.002 |
| 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 | 0.001 | 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".