Representative bureaucracy in Canada: multiculturalism in the public service
Bibliographic record
Abstract
As the population in many western democracies becomes increasingly diverse as a result of global migration, national governments are challenged with settling and integrating minority groups into mainstream society. Yet accomplishing sustainable integration is difficult and issue-laden, as anti-immigrant sentiments, discrimination and barriers to employment, tokenism, and a lack of opportunities continue to affect minority participation in the host society. In that respect, Canada has adopted Multiculturalism as a public policy instrument to nation-building. In order to meet the needs of its diverse population, Canada has also implemented Employment Equity in its civil service as a measure to achieve representative bureaucracy among its cadre of civil servants. To date, the Canadian Multiculturalism policy has been met with a relative degree of success in comparison to other countries with strong immigrant receiving traditions. This comparative level of success is due in part to Canada’s emphasis on immigrant integration (vis-a-vis assimilation) where both host group members and minority group members adopt and adapt to each other’s cultures. This chapter details how Canada’s unique English and French roots, immigration history, and pluralist view of citizenship have allowed Multiculturalism to be deployed as a public policy tool to successfully integrate minorities and citizens with immigrant backgrounds in comparison to other countries. We also discuss how Multiculturalism has been used to mitigate some of the issues which arise from diverse workforces. We close with a review on how Canada has engaged its civil service to help achieve its ideals as a multicultural nation.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".