Because we said "I do": what factors are challenging Roman Catholic marriages in the Diocese of Charlottetown, and what steps can be taken to help them?
Bibliographic record
Abstract
This thesis researches marriages in the Diocese of Charlottetown. The student chose this direction because people in the diocese were coming to him for marriage counselling. A wide variety of marital issues could have been researched; however, dynamic feedback received from the diocese-wide marriage survey highlighted three key areas for further examination. Areas of recurring struggle revealed in the survey were inability to resolve conflict, inability to engage in marital conflict in a healthy manner, and the lack of ongoing support for newly married couples. The survey also revealed that no consistent form of premarital counselling was present in the Diocese of Charlottetown. The student developed recommendations and interventions for the identified areas of struggle. The student's own clinical, theological, background aided in the development of the interventions. The student believes that tailored strategies, derived from analysis of the diocesan-wide survey and joined to an existing premarital counselling program, would strengthen marriages in the diocese and prevent marital crisis later. The student chose to join his recommendations and interventions to the premarital counselling program "Beloved."
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".