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Record W2148510600 · doi:10.1080/15332691.2010.515532

Emotionally Focused Couple Therapy: A Full-Treatment Model Well-Suited to the Specific Needs of Lesbian Couples

2010· article· en· W2148510600 on OpenAlexaff
Karen Hardtke, Michael S. Armstrong

Bibliographic record

VenueJournal of Couple & Relationship Therapy · 2010
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsUniversity of OttawaYork University
Fundersnot available
KeywordsLesbianPsychotherapistPsychologyDistressPsychological interventionPopulationClinical psychologyPsychoanalysisMedicinePsychiatry

Abstract

fetched live from OpenAlex

During the past decade, the psychology literature on lesbian couples and families has mushroomed. Despite this growth, the translation of lesbian couple research to therapy practice has been a slow process. No empirical studies of a full-treatment model have been conducted to determine the most effective interventions with lesbian couples seeking treatment for relationship distress. In this article, we begin to address the paucity of literature in this area and we argue that the theoretical underpinnings of emotionally focused couple therapy (EFCT) is particularly well-suited to the unique needs of lesbian couples. In doing so, we also hope that this theoretical discussion will serve to stimulate empirical investigation, ultimately leading to the identification of best practices with this population.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.055
GPT teacher head0.363
Teacher spread0.307 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations28
Published2010
Admission routes1
Has abstractyes

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