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Record W3134374670 · doi:10.1521/jsyt.2020.39.4.1

“I Am Tensing”: Thoughts on Active and Passive Language in the Description and Expression of Emotion in Psychotherapy

2020· article· en· W3134374670 on OpenAlexvenueno aff
Andrew E. Roffman

Bibliographic record

VenueJournal of Systemic Therapies · 2020
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsExpression (computer science)PsychologyPromotion (chess)Emotional expressionPsychotherapistMindfulnessSocial psychologyComputer sciencePolitical science

Abstract

fetched live from OpenAlex

My intention in writing this paper is to outline the different effects of active and passive language use in psychotherapy when it comes to the expression and description of emotion. I will argue for the value of helping clients shift from passive to active language as they describe their emotional experience; that this shift deepens a client's engagement in the moment, allowing for embodiment, ownership, and accountability especially regarding distressing emotion. I will describe how mindfulness adds a further step in deepening this process. I will offer exceptions for the promotion of active over passive language, as well as an exercise so that readers may experiment with similar shifts in their own emotional expression as a means of having a direct experience of the effects of active language.

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 score0.568
Threshold uncertainty score0.230

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 science0.0000.000
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 head0.030
GPT teacher head0.320
Teacher spread0.291 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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