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Record W7000953374

How Do Psychoanalytic Mental Health Clinicans’ Reactions, Understandings and Formulations Shape Their Work with Gender-Creative LGBTQ+ Clients?

2023· article· en· W7000953374 on OpenAlexaboutno aff

Bibliographic record

VenueSmith ScholarWorks (Smith College) · 2023
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPsychoanalytic theoryConceptualizationMental healthAlliancePrejudice (legal term)Diversity (politics)White (mutation)Face (sociological concept)
DOInot available

Abstract

fetched live from OpenAlex

This study investigates the ways in which psychoanalytic mental health clinicians in North America (United States and Canada) face and manage prejudices targeting gender diversity with LGBTQ+ clients, and what they do or do not do to prevent and repair ruptures in the therapeutic alliance through latrogenic gender enactments. The predominantly white sample was comprised of psychoanalytic clinicians: members of the International Psychoanalytical Association that trained and practices in the United States and Canada, and the years of experience oscillated between 3 and 48 years. There were 20 eligible participants for a 60- to 90-minute semi-structured interview; 14 males and 6 females. Ten participants out of the 20 identified as queer, gay, bisexual and/or trans. The results support current trends in prejudice studies that recommend symbolic relationships with members of the prejudiced-against community to achieve the dismantling of internalized prejudices. It provides evidence of the importance of accessibility at all levels of institutional psychoanalysis to address systemic prejudices that impact the training of beginning clinicians and deter LGBTQ+ people from accessing psychoanalytic treatments that can be beneficial. Lastly, participants strongly advocated for a revision of pedagogic curricula that includes a less harmful conceptualization of gender and sexual diversity.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.422
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.063
GPT teacher head0.359
Teacher spread0.296 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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