One-Person Households in Canada and the Implications for Health: A Health Geography Perspective
Bibliographic record
Abstract
In recent decades, one-person households (OPHs) have become increasingly prevalent in developed countries, including Canada. Health concerns among individuals living alone in OPHs have also been highlighted. Despite this global recognition, such issues have received limited attention in Canada, and existing literature primarily focuses on older adults and overlooks other age groups. This thesis comprehensively examines the phenomenon of OPH in the Canadian context through a health geography perspective, utilizing data from the 1991-2016 Canadian Census Public Use Microdata Files and the 2017-2018 Canadian Community Health Survey Public Use Microdata File. Through descriptive analysis and binary logistic regression, this study identifies temporal-spatial trends in OPH prevalence and assesses the health implications of living in an OPH, across all adult age groups nationally. This analysis reveals a consistent increase in the prevalence of OPHs among Canadian adults from 1991 to 2016, primarily driven by rapid growth among middle-aged individuals. The Atlantic Provinces and Quebec exhibit the fastest growth in OPHs across all age groups. While OPH living remains primarily an urban phenomenon among young adults, it has seen a growing presence in rural areas among middle-aged and older adults in recent years. Compared to living with others, living alone in an OPH is detrimental to the health of Canadian adults, although the severity and underlying mechanisms of this detriment vary among age groups. Poorer socioeconomic conditions and unhealthy lifestyles emerge as significant risk factors for the OPH population across all age groups. Sex, ethnicity, marital status, personal income, access to regular health care providers, and the place of residency have different impacts across the three age cohorts (young adults, middle-aged adults, and older adults). These findings address critical research gaps and provide valuable insights for policymakers to effectively respond to the rapidly growing phenomenon, promoting the health and well-being of the OPH population in Canada.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.016 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".