Bibliographic record
Abstract
People believe that if love and romance in courtship can be retained, marriages can be a life-long engagement. However, increasing numbers of divorces, extramarital relationships, marital conflicts, family violence and family tragedies suggest that as marital life goes on, the couple relationship cannot always be maintained as it was. Two people who enter a marriage will change and their relationship will also change. A personal change for one partner interactively affects the equilibrium of the marital relationship. Marital couples need to recognise that a marriage is not a static state but a dynamic relationship. This paper is an attempt to challenge some of the popular myths of marriage and to present a new paradigm which is termed Dynamic Marriage. This new paradigm is a reconstruction of the marriage concept from a static view to a dynamic perspective, with emphases on the following seven areas: (i) maintenance versus development; (ii) decrease in love versus increase in commitment; (Hi) depending on fate versus a need to learn; (iv) demanding the partner to change versus developing shared goals; (v) problem-conscious versus enrichment- oriented; (vi) security versus new way of life; (vii) private matters versus sharing with others.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.003 | 0.014 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".