The IPscope: Applications to Couple and Family Therapy Supervision
Bibliographic record
Abstract
The IPscope (IP signifying Interpersonal Patterns), developed at the Calgary Family Therapy Center by Karl Tomm and colleagues, provides a way of understanding behavior in context. Building on our work using the IPscope to conceptualize the functioning of families, we have also used the IPscope to bring a relational ethos to CFT supervision. After describing the development of the IPscope and its use at the CFTC, we describe specific applications of the IPscope to several key foci of clinical supervision: cross-cultural issues; the supervisory working alliance, with specific reference to supervisee nondisclosure and informal supervision; supporting supervisees to develop case conceptualization skills with the IPscopic reflectogram; dealing with impasses in therapy or supervision, usually labeled intrapsychically as countertransference, and a practical approach to isomorphism. Finally, we address limitations and critique of the IPscope.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".