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Record W4322494975 · doi:10.34296/04s11076

Sex-Positive Clinical Supervision: A Special Commentary

2023· article· en· W4322494975 on OpenAlexaff
Beda A. Bjorn

Bibliographic record

VenueJournal of Counseling Sexology and Sexual Wellness · 2023
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsYorkville University
Fundersnot available
KeywordsConceptualizationClinical supervisionSupervisorCompetence (human resources)PsychologyIntervention (counseling)Mental healthThematic analysisPsychotherapistMedical educationMedicineQualitative researchPsychiatrySocial psychologyManagementSociology

Abstract

fetched live from OpenAlex

This commentary focuses on clinical competencies, research frameworks, training implications that elevate the meta-competence awareness for the clinical supervisor. There is an identified need to expand sex-positive clinical supervision guidelines. The supervisory setting is created for the safety and personal-professional growth of the supervisee, where it is an opportunity to conceptualize the thematic development of our clinical evolution. In this space, we set a foundation for clinical frameworks to guide the applicability of specific intervention methods and strategies that allow for the critical formulation of a healthy therapeutic outcome. Without established and robust sex-positive frameworks in supervision, the clinical supervisor is exposed to incompetent practices that miss an adequate assessment, detection, and treatment, all critical elements of the conceptualization process. To make matters worse, the lack of training and preparation in sexual wellness and other sexual topics is transferred onto the supervisee, creating a circuit of uninformed clinicians and left to fend on their own when encountering a future client seeking treatment. Not only are we causing a disservice to our supervisees, but we are perpetually injuring the clinical community as a whole. This commentary will examine the clinical, research and training priorities in clinical mental health counseling.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.696
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.377
Teacher spread0.332 · 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.

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

Citations1
Published2023
Admission routes1
Has abstractyes

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