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Application of Emotion-Focused Therapy in Bereavement: a Case Study

2009· article· en· W1895584055 on OpenAlex
Jianxiu Gao

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian social science · 2009
Typearticle
Languageen
FieldPsychology
TopicChild Therapy and Development
Canadian institutionsnot available
Fundersnot available
KeywordsPsychotherapistPsychologyHumanitiesCoping (psychology)Family therapyArt

Abstract

fetched live from OpenAlex

This paper presents a single case study of a woman who losing family members. Emotion-Focused Therapy provides an effective treatment methodology and technique for working through this situation. Emotion-Focused Therapy impact grief work proceeds through management of affect, assimilation and acceptance of the implication of the losses, resolving related issues, restructuring and development of coping capacities, establishment of new life goals and styles. Key words: Emotion-focused therapy, Bereavement, Losing Resume: Cet essai presente une etude d’un cas d’une femme qui a perdu les membres de sa famille. La therapie concentree sur l’emotion offre une methodologie et technique de traitement effective. L’impact de cette approche therapeutique sur la douleur se produit par le biais de la gestion des emotions, l’assimilation et acceptation de l’implication des pertes, la resolution des problemes concernes, la restructuration et le developpement des capacites de se debrouiller, l’etablissement des objectifs et styles de la vie. Mots-Cles: therapie concentree sur l’emotion, deuil, perte

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.834
Threshold uncertainty score0.944

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.023
GPT teacher head0.321
Teacher spread0.298 · 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