Supports and limitations of aging in a rural place for women aged 85 and older
Bibliographic record
Abstract
Women over the age of 85, living in a rural environment, such as that of Atlantic Canada, are often considered to be an invisible cohort. This invisibility is primarily due to social isolation which occurs when older adults lose members of their social networks, including friends and family. As suggested by Walkner and colleagues (2018) this issue is compounded for those living in rural areas since geographical distance from others and lower populations pose additional challenges to daily social interaction. This is significant for elderly women, as they generally outlive their male partners, and staying connected to familiar surroundings is crucial to positive aging (Loe, 2010). For example, in Prince Edward Island (PEI), women account for 67% of people who are 85 and older (Statistics Canada, 2017b). Between 2011 and 2016, the number of Canadians aged 85 and older grew by 19%, which is nearly four times the rate for the overall Canadian population (Statistics Canada, 2017a). Furthermore, the Canadian population aged 85 and older is expected to triple when baby boomers begin to reach this age group in 2031 (Statistics Canada, 2012). Considering this shift in population distribution, it is important to recognize that women comprise a larger proportion of older adults because they are more likely to live longer. This imbalance will have serious sociodemographic impacts as women will have higher levels of frailty, depression, and widowhood while having less education (Weir, 2014; Strömquist, 2015). Recognizing the importance of societal awareness of this cohort is imperative as women are twice as likely to be poor as a result of having lower incomes from pensions, which can be attributed to interruptions in their careers to take care of children and other family members (Silver, 2003; Kim et al, 2013; Weir, 2014; Strömquist, 2015; Statistics Canada, 2017a).
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".