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Record W2165940322 · doi:10.1177/0011000009339341

Korean Supervisors’ Experiences in Clinical Supervision

2009· article· en· W2165940322 on OpenAlexaff
Jeeseon Park

Bibliographic record

VenueThe Counseling Psychologist · 2009
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsMcGill University
Fundersnot available
KeywordsPsychologyMental healthClinical supervisionContext (archaeology)Counseling psychologyMedical educationApplied psychologyPsychotherapistMedicine

Abstract

fetched live from OpenAlex

The demand for mental health services in Korea is increasing, and a corresponding rise in the number of trainees in counseling psychology results in a need for effective supervision. Using a grounded theory approach, this study explored Korean supervisors’ experiences in supervision to better understand the current status of supervision practice in Korea. A model emerging from the data suggests that Korean clinical supervisors in mental health view teaching and explorations of supervisees’ personal issues as the main activities of supervision. Both the method of supervision and the structure of supervision affected the way that supervisors’ theoretical orientations and supervisees’ developmental levels influenced the focus of supervisors’ teaching and explorations of supervisees’ personal issues. To compensate for lack of formal training in supervision, participants in this study engaged in self-development activities. The results of this study are discussed in the context of Korean cultural characteristics and the current status of counseling psychology in Korea. Implications for future supervision training in Korea and in the United States are discussed.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.005
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.001
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 head0.088
GPT teacher head0.416
Teacher spread0.328 · 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

Citations44
Published2009
Admission routes1
Has abstractyes

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