Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".