Canada's 150th Anniversary Multiculturalism and Diversity: Vehicles for Sustainable Socio-Economic Progress/150e Anniversaire Du Canada: Multiculturalisme et Diversite: Vehicules De Progres Socioeconomique Durable
Bibliographic record
Abstract
ABSTRACT Using a multi-disciplinary approach, this article briefly discusses the socio-economic implications of Statistics Canada's demographic projections for Canada in 2017, followed by a presentation of three challenges facing the country over the next ten years: the demographic challenge, the human capital challenge, and the citizenship and identity challenge. ********** Cultures of uniformity around the world are giving way to multi-racial, multiethnic, and multi-religious national societies. As recently as 1960, the advanced Western industrial states were more or less homogenous, owing either to legal or customary exclusion or to physical isolation. Now, not only ideas but also individuals and their families (with skills for the new economy) are spreading throughout the world, changing the assumptions of the societies and cultures that receive and welcome them (Worm Economic Forum 2001). Enhancing Canadian citizenship and identity, arts and culture, youth and sports, and diversity and multiculturalism all go hand-in-hand with aiding vulnerable citizens to meet their basic needs and become stronger citizens. Basic needs, such as education, health care, employment, and civic-read political-participation, should be met to help build an inclusive society where all Canadians share in, and contribute to, cultural, social, and economic life. RELEVANCE OF 2017 A look at Canada's medium- to long-term future in light of socio-economic changes and demographic projections is needed. Policy-makers and applied researchers need to address issues closer to hand and start planning ahead, especially after years of inaction. Short-term and current actions and policies should be balanced with long-term prospects for prosperity and sustainable development. In fact, it is now habitual for countries everywhere, equipped with powerful informatics abilities, to look twenty and thirty years down the road. By 2017, 20-25 percent of all Canadians will be members of visible minority groups, a ratio that is much higher in some major cities (e.g., over 50% of the population in Toronto and Vancouver); by 2011, immigration will be the sole source of net labour-force growth, and almost 90 percent of these immigrants will be minorities; by the year 2025, immigration will be the source of all population growth. Both Aboriginal peoples and visible minorities have more youthful populations compared to the rest of the population; they also have higher fertility rates compared to a Canadian average of less than 1.5 children per woman (Statistics Canada 2003b). An effective approach is needed to face up to the challenges of the changing demographics of Canada in the next two decades. This approach should start with recognition, especially by policy-makers at the highest level, of the new and dynamic portrait of Canada. Canadian diversity, multiculturalism, and equality policies have been applied timidly. Diminishing the profile of such policies and programs is not the answer. While Canada is rapidly becoming a multi-racial, multi-religious, and multi-cultural country, an ostrich approach, whether from government at all levels or from a corner of the mainstream society, is not recommended. This kind of avoidance could be viewed as resistance to socio-demographic change in the interest of maintaining the country's current power structure. Socio-economic problems manifest themselves as emergencies over the course of a single year (natural disasters, labour strikes, epidemics, unemployment, poverty, fiscal and monetary policies, etc.). In contrast, demographic issues deal in generations (the ability of a couple to reproduce themselves) that could be periods of twenty-five years. The year 2017, ten years away from our 2007 perspective, falls within the current generation and should be considered the near future, and thus worthy of immediate consideration. Addressing the challenges of 2017 is not a luxury, but a necessity; countries embark on the study of their future as a standard feature of policy-making. …
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".