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Record W3087869491 · doi:10.1558/cam.34100

Change in Family Therapy

2020· article· en· W3087869491 on OpenAlexaff
Peter Muntigl, Adam O. Horvath

Bibliographic record

VenueCommunication & Medicine · 2020
Typearticle
Languageen
FieldPsychology
TopicCounseling, Therapy, and Family Dynamics
Canadian institutionsSimon Fraser University
FundersStrongHarvard UniversityUniversity of PennsylvaniaUniversity of CambridgeAmerican Psychiatric Publishing
KeywordsFamily therapyMedicinePsychologyPsychotherapist

Abstract

fetched live from OpenAlex

A fundamental theoretical premise in Structural Family Therapy (SFT) is that changes in individual members and improvements in intra-familial relations are realized by repairing the family structure. Dysfunctional families are conceptualized in terms of individuals taking on inappropriate roles (e.g., children acting as if they were parents) and the boundaries between parental executive levels and the children/sibling level are unclear, too rigid, or highly permeable. The therapist's role is to temporarily engage (join) with family members in a way that generates in-session interactions that exemplify the desirable family structure. While the theory supporting these interventions are well developed, there has been little work done on explicating how such tasks may be interactively accomplished in clinical practice. Drawing from the methods of conversation analysis, our aim for this paper is to show how a master therapist in SFT accomplishes some of these transformations during a single therapy session. We focus on the discursive resources through which the therapist is able to readjust the role relationships between a mother and her daughter (i.e., in such a way that the mother can adopt a more agentive position vis-a-vis her children) and how the therapist's actions indexed core SFT principles of restructuring the family.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.643
Threshold uncertainty score0.725

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.156
GPT teacher head0.385
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2020
Admission routes1
Has abstractyes

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