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Record W2128506299 · doi:10.7202/032214ar

Le thérapeute conjugal est un cheval de Troie : Réflexions inspirées des résultats de recherches sur l’intervention auprès des couples

2007· article· fr· W2128506299 on OpenAlexaffvenue
Jean-Marie Boisvert, Madeleine Beaudry

Bibliographic record

VenueSanté mentale au Québec · 2007
Typearticle
Languagefr
FieldPsychology
TopicPsychoanalysis and Psychopathology Research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsArtHumanitiesGynecologyMedicine

Abstract

fetched live from OpenAlex

Communication training and positive exchange training are the two methods for improving marital relations that research has established as being the most effective. However, even after conducting therapy involving both partners based on these methods, too few couples (35%) succeed in reaching the same level of satisfaction as couples who are already satisfied with their relationship. The efforts that have been undertaken to increase this rate have focused mainly on developing new therapeutic techniques that include cognitive, emotional and systemic approaches. However, the results of experimental studies to date do not prove the superiority of these new approaches. Given this situation, it is time to pay more attention to particular characteristics of the therapeutic relation in marital therapy and to the means of obtaining the collaboration of the two spouses. As is the opinion of certain authors, the most difficult clinical task does not consist of finding what the clients must do to solve their problems, but rather to determine how to motivate them and help them achieve their goal. An analysis of this task, based on clinical observations and results of recent research in this area, has allowed the authors to present a number of hypotheses about ways to reinforce the therapeutic alliance and eventually reduce the failure rate of marital therapy.

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)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.599
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.076
GPT teacher head0.396
Teacher spread0.320 · 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.

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

Citations1
Published2007
Admission routes2
Has abstractyes

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