Investigating counselor training environment, awareness of privilege, and social dominance orientation as predictors of counselor trainees' self-reported multicultural competencies
Bibliographic record
Abstract
Despite the elapsed 33 years since the delineation of the Multicultural Counseling Competencies (Sue et al., 1982), little is known about factors that may facilitate the development of multicultural competence in counselors and counselor trainees. As a first step toward greater empirical understanding of multicultural competence and training, the present study sought to examine 3 predictors of counselor trainees’ self-reported multicultural competencies. It was hypothesized that trainees’ Social Dominance Orientation, as measured by the Social Dominance Orientation Scale (SDO6, Sidanius & Pratto, 1999); Awareness of White Privilege, as measured by the White Privilege Awareness subscale of the Privilege and Oppression Inventory (POI; Hays, Chang, & Decker, 2007); and the Multicultural Training Environment of trainees’ graduate programs, as measured by the Multicultural Environmental Inventory—Revised (MEI-R; Pope-Davis, Liu, Nevitt, & Toporek, 2000), would significantly contribute to their self-reported multicultural competencies, both together and individually. Counselor trainees (N = 362) from doctoral and Master’s-level training programs in the U.S. and Canada completed the online survey. Awareness of White Privilege and Multicultural Training Environment were supported as predictors of trainees’ self-reported multicultural competencies, and social dominance orientation was partially supported, suggesting that each predictor bears an important relationship with self-reported multicultural competencies; that is, lower social dominance orientation, higher awareness of white privilege, and greater perceived attention to multicultural issues in the graduate training environment were related to higher self-reported multicultural competencies amongst counselor trainees. More importantly, however, significant measurement issues in the field of multicultural competence were encountered; thus, while these three predictors of self-reported multicultural competencies are important to theory building, it is posited that research on the multicultural competencies cannot move forward until these substantial measurement issues are addressed.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".