Bibliographic record
Abstract
Canada's population is aging. Demographic findings released by Statistics Canada project the 65 years and older population to rise from 3.92 million in 2001 to roughly 9.2 million people by 2041, or approximately one in four Canadians. The median age for the Canadian population has increased from 29 years old in 1981 to 39 in 2005. Over the same time period, the youth-dependency load, those aged 0 to 14 years of age, as a percentage of the population shrank by 5 percent. This shift in the demographic profile has serious policy implications for Canada. Canadian policymakers will have to deal with both a shrinking labor force and an increased burden on social services. Though the ultimate causes of the increasing aging of the population are hard to pinpoint, the approximate causes of Canada's senescence are clear--a low mortality rate along with declining birth rates has produced an age distribution with fewer younger-aged cohorts and more old-aged cohorts. Improvements in medical technologies, public health, and hygiene over the last few centuries, along with a host of other factors, have led to lower overall mortality. Furthermore, a decreased need to have more children to ensure infant survival, wider availability of contraceptives, and greater female involvement in the labor force over the last 50 years are also causes for lower fertility rates. Those in prime child-bearing years such as those aged 20 to 24 have seen birth rates plummet from just over 20 percent in 1956 to around 5 percent in 2003. Lower old-age mortality and higher life expectancy pose serious challenges to Canada's social security system and public finances. The Canadian Pension Plan (CPP), Canada's pension system, will now require reform in order to remain solvent in the future. As Canada's workforce begins to shrink and the number of social security dependents increases, CPP will be unable to cope with larger social security disbursements and fewer received payments. The dependence of senior citizens on social security in Canada makes sustainability all the more important. Roughly half of a Canadian old-age retiree's income comes from social security disbursements from CPP and from Old-Age Security payments, which provide a supplement to CPP income for retirees. For female senior citizens, 60 percent of their incomes come from CPP and Old-Age Security payments. While there have been serious considerations to begin investing pension contributions to convert the CPP into a partially funded system, this will only mitigate but not solve the problem of higher levels of payments and lower levels of revenues funding those payments. …
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.007 | 0.002 |
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; both teacher heads agree on what is shown here.
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".