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Record W2510509034 · doi:10.1080/14681994.2016.1193133

Inclusive sex therapy practices: a qualitative study of the techniques sex therapists use when working with diverse sexual populations

2016· article· en· W2510509034 on OpenAlexaff
Michael D. Berry, Anastasia Natasha Lezos

Bibliographic record

VenueSexual & Relationship Therapy · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMarriage and Sexual Relationships
Canadian institutionsMcGill University Health CentreMcGill University
Fundersnot available
KeywordsSex therapyPsychologyQualitative researchClinical psychologyPsychotherapistDevelopmental psychologySexual dysfunctionPsychiatrySociology

Abstract

fetched live from OpenAlex

Attention to the clinical needs of diverse client populations, including lesbian, gay, bisexual, trans* and queer (LGBTQ) clients, openly non-monogamous clients, and bondage and discipline, sadism and masochism (BDSM) lifestyle clients, has grown in recent years. This study reports interview-based qualitative research findings, from a sample of sex therapy specialists and subject-matter experts (n = 34), on key clinical principles and practices used in the treatment of such diverse client groups. Three clinical principles are identified: therapist self-reflection, client-affirmation, and normalizing. Core clinical techniques to support these overarching principles are then described and discussed. The utility of such techniques, and relevant treatment considerations in inclusive sex therapy practice with diverse clients, are evaluated in relation to interview data.

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)0.016
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0120.013
Scholarly communication0.0040.004
Open science0.0020.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.316
GPT teacher head0.448
Teacher spread0.133 · 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 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

Citations12
Published2016
Admission routes1
Has abstractyes

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