How Do Organizations and Social Policies ‘Acculturate’ to Immigrants? Accommodating Skilled Immigrants in Canada
Bibliographic record
Abstract
While the idea of acculturation (Berry 1997) was originally proposed as the mutual change of both parties (e.g., immigrants and the host society), the change processes of host societies are neglected in research. A grounded theory study explored the efforts of human service organizations to 'acculturate' to an increasingly diverse immigrant population, through interviews conducted with service providers serving Mainland Chinese immigrants. Acculturation efforts of human service organizations (mezzo-level acculturation) were often needs-driven and affected by the political will and resultant funding programs (macro-level forces). Even with limitations, human service organizations commonly focused on hiring Mainland Chinese immigrants to reflect the changing demographics of their clientele and creating new programs to meet the language and cultural backgrounds of the clients. To contextualize these organizational efforts, an analysis of how policy changes (macro-level acculturation) interact with organizational practice is presented. Finally, the meaning of acculturation for the host society is discussed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".