Bibliographic record
Abstract
This article addresses conditions for inclusive policy making in multicultural societies. It focuses on and compares development of health policies in Australia and Canada, asking whether paying greater attention to cultural competence could enhance deliberative health policy development by improving inclusion of people from culturally and linguistically diverse (CALD) backgrounds. Answering this question brings together insights suggested by critical multiculturalism, deliberative democracy, and public administration. Reviewing policy frameworks and interviewing health policy officers in both countries underpinned a critical examination of national and sub-national governments to understand barriers to and enablers of inclusive citizen engagement. Defining culture as relational and changeable, it became apparent that many Australian and Canadian health agencies perceive multicultural policy as a means of managing and controlling diversity rather than a mechanism to improve democratic participation. A critical multicultural perspective promotes consideration of context, challenging individual and organizational histories and assumptions, organisational processes and procedures, to understand how current modes of operating and thinking impact on CALD citizens. The article suggests shifting focus from "cultural competence" towards contextual sensitivity, the promise of which lies in encouraging awareness of citizens as individuals, for whom culture is just one of many influences shaping their position in society.
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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 | 0.076 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.043 |
| Scholarly communication | 0.017 | 0.010 |
| Open science | 0.002 | 0.023 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".