Reconnecting with relational values in highly conflicted separating couples: A narrative therapy‐informed relational interviewing teamwork‐based supervision approach
Bibliographic record
Abstract
This article outlines a new supervision practice of narrative therapy-informed reflecting team-based relational interviewing for a high-conflict stuck case of a separated middle-aged couple. The article demonstrates the supervision method consisting in five parts. First, the supervisor interviews the couples' relationship while the team watches from behind the one-way mirror. Second, the team responds to the interview while the couple and the supervisor witness their conversation. The couple is then invited to respond back to the team. Furthermore, there is a meta-conversation about the supervision in collaboration with the couple. The intervention ends with therapeutic letter writing to the relationship. The couple showed a meaningful shift in their positioning towards a more relational awareness and found valuable ways for continuing their therapy. The theoretical elements of the approach underpinning practice to tackle high conflict are considered through the illustration of the case.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".