Valuing the Contributions of Family Caregivers to the Care Economy
Bibliographic record
Abstract
Abstract The purpose of this paper is to estimate the monetary value of Canadians’ family care work, to highlight inequalities within the family care sector and place this work within the care economy. Using Statistics Canada’s 2018 General Social Survey, we estimated the replacement cost of the 5.7 billion hours of respondents’ care work at between $97.1 billion and $112.7 billion. We used descriptive, backward stepwise regression and dominance analyses to examine the distribution of care responsibilities among caregivers. Caregivers comprised 22.1% of the sample (6.8 million Canadians). Living arrangement explained most (81-83%) of the variance in the value of unpaid care work, followed by generation (14-15%), income (2%) and gender (1-2%). These findings provide powerful evidence of the economic value of family care work and of the inequalities among family caregivers in the magnitude of their contributions. Monetizing the value of family care makes it more visible, locates it in the context of the broader care economy and establishes its relationship to the much more visible and valued realm of paid care work. This contextualization also responds to global action plans and resolutions urging governments to create systems of long-term and continuing care for people with chronic conditions and disabilities rather than imposing sole responsibility on unpaid caregivers.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".