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Record W4281485178 · doi:10.1177/00221678221099679

Multicultural Competence as a Common Factor in the Process and Outcome of Counseling

2022· article· en· W4281485178 on OpenAlex
Geoff J. Bathje, Daniel Pillersdorf, Hadeel Eddir

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Humanistic Psychology · 2022
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsPsychologyCompetence (human resources)MulticulturalismEthnic groupClinical psychologyPath analysis (statistics)Therapeutic relationshipSocial psychologyPsychotherapist

Abstract

fetched live from OpenAlex

Much research has been conducted on multicultural competence (MCC) over the past four decades, though there is still a need to conduct further research into the role of MCC within actual counseling relationships and in relation to additional variables. The present survey study was designed to better elaborate on the relationship between MCC and several common factor therapy and outcome variables within counseling relationships. Findings indicated that MCC was more strongly correlated with all measured variables (except perceived change) within counseling relationships where client and/or counselor identified as BIPOC than in White–White client counselor dyads. MCC was associated with higher ratings on the other measured variables regardless of client–counselor race or ethnicity. Finally, path analysis supported a model where MCC (a therapist factor) influenced process factors, which in turn influenced therapeutic outcomes. The results provide support for the importance of MCC to the process and outcome of counseling, particularly for BIPOC clients.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.500
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.062
GPT teacher head0.423
Teacher spread0.360 · 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