General Social Survey, 2012 [Canada]: Cycle 26, Caregiving and Care Receiving
Bibliographic record
Abstract
This survey collects data on the situation of Canadians who receive help or care because of a long-term health condition, a disability or problems related to aging, and of those who provide help or care to family members or friends with those conditions. Data from this survey will help us to better understand the needs and challenges faced by these Canadians, and allow policy makers to design programs that meet their needs. Questions in the survey cover the types and amount of care family caregivers provide, the kinds and amounts of care Canadians receive, and the unmet needs of those who need care but are not receiving it. An expanded set of questions covers the impact of caregiving on various aspects of the lives of caregivers. All respondents will be asked questions about their overall health, employment, housing and other socio-demographic characteristics such as birth place, religion and language. Results from this survey will be used by analysts and researchers to study current situations and trends, and by many government departments to develop policies and programs that can have an impact on individuals who receive care, their families, those who provide care, and those who may need or provide care in the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.023 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.022 | 0.012 |
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".