Cross-cultural communication in social work practice: An interpretive approach to cross-cultural communication difficulties.
Bibliographic record
Abstract
This research is focused on cross-cultural communication misunderstandings between First Nations people, living on reserve, and outside services/agencies. The goal of the research is to consider issues related to cross-cultural communication. The findings are important for social workers engaged in community practice roles. An interpretive descriptive approach was used to explore the issue. The data were taken from participant interviews and thematic analysis was used to identify themes. Four themes emerged from the interviews: transportation to urban services and technology, cultural practices, language and translation, and jargon and slang. The themes provide insight into how cross-cultural communication misunderstandings and professional practice applications impact relationship building between social workers and their clients.--P.ii.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.049 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.013 | 0.048 |
| Scholarly communication | 0.023 | 0.024 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".