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Record W4352976650 · doi:10.1080/08351813.2023.2170663

Responding to <i>In-the-Moment</i> Distress in Emotion-Focused Therapy

2023· article· en· W4352976650 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueResearch on Language and Social Interaction · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsYork UniversityUniversity of TorontoSimon Fraser University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsImmediacyDistressPsychologyPsychotherapistConversation analysisIntervention (counseling)Embodied cognitionSocial psychologyApplied psychologyCommunicationConversationComputer science

Abstract

fetched live from OpenAlex

Emotion-focused therapy offers a setting in which clients report on their personal experiences, some of which involve intense moments of distress. This article examines video-recorded interactional sequences of client distress displays and therapist responses. Two main findings extend understanding of embodied actions clients display as both a collection of distress features and as interactional resources therapists draw upon to facilitate therapeutic intervention. First, clients drew from a number of vocal and nonvocal resources that tend to cluster on a continuum of lower or higher intensities of upset displays. Second, we identified three therapist response types that oriented explicitly to clients’ in-the-moment distress: noticings, emotional immediacy questions, and modulating directives. The first two action types draw attention to or topicalize the client’s emotional display; the third type, by contrast, had a regulatory function, either sustaining or abating the intensity of the upset. Data are in North American English.

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 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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.215
GPT teacher head0.474
Teacher spread0.259 · 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