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Record W2032857080 · doi:10.1111/jmft.12110

Internalized Other Interviewing in Relational Therapy: Three Discursive Approaches to Understanding its Use and Outcomes

2015· article· en· W2032857080 on OpenAlexaff
Tanya Mudry, Tom Strong, Inés Sametband, Marnie Rogers‐de Jong, Joaquín Gaete, Samantha Merritt, Emily M. Doyle, Karen H. Ross

Bibliographic record

VenueJournal of Marital and Family Therapy · 2015
Typearticle
Languageen
FieldPsychology
TopicCounseling, Therapy, and Family Dynamics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsConversationInterviewMotivational interviewingPsychologyConversation analysisSocial psychologyIntervention (counseling)Family therapyFamily memberPsychotherapistSociologyMedicineCommunicationFamily medicinePsychiatry

Abstract

fetched live from OpenAlex

For over 20 years, family therapist Karl Tomm has been engaging families and couples with a therapeutic intervention he calls Internalized Other Interviewing (IOI). The IOI (cf. Emmerson-Whyte, 2010; Hurley, 2006) entails interviewing clients, from the personal experiences of partners and family members as an internalized other. The IOI is based on the idea that through dialogues over time, one can internalize a sense of one's conversational partner responsiveness in reliably anticipated ways. Anyone who has thought in a conversation with a family member or partner, "Oh there s/he goes again," or anticipates next words before they leave the other's mouth, has a sense of what we are calling an internalized other. For Tomm, the internalized anticipations partners and family members may have offers entry points into new dialogues with therapeutic potential-particularly, when their actual dialogues get stuck in dispreferred patterns.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.441
GPT teacher head0.339
Teacher spread0.102 · 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 designObservational
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

Citations12
Published2015
Admission routes1
Has abstractyes

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