Multiparty Talk in Family Therapy: Complexity Breeds Opportunity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Discursive investigations of multiparty talk can aid family therapists. In this article, discourse analysis was used to demonstrate how a therapist and family members concurrently engage multiple conversational partners to accomplish forward movement after conversational impasses. By looking closer at conversational practices, therapists can become more aware and creative as they attempt to move forward with clients. With the microlens cultivated in a discursive analysis, therapists can adopt alternative “conversational courses of action” as they become more sensitive to constructing “interventions” with clients. With this sensitivity, it is less likely that therapists will label clients resistant as they learn to become more resourceful and conversationally adaptive participants in stalled conversations. They may then better position themselves to recognize the enormous, often previously unnoticed, opportunities to join family members in multiparty talk.
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.
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 | 0.002 | 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 | 0.001 |
| Open science | 0.001 | 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 it