Multigenerational Living and Children’s Risk of Living in Unaffordable Housing: Differences by Ethnicity and Parents’ Marital Status
Bibliographic record
Abstract
A growing share of Canadian households are living in unaffordable housing (i.e., spending 30% or more of their pre-tax income on housing costs). During this time, the prevalence of multigenerational living has also increased. Ethnic minority families are more likely than White families to live in multigenerational households. These trends raise the questions: (a) is multigenerational living a strategy for families to navigate the housing affordability crisis? (b) do ethnic minority children benefit more from multigenerational living than their White peers? Using confidential data from the 2016 Canadian Census, we examine how multigenerational living shapes the housing experiences of children under the age of 16. Multigenerational living is associated with consistent reductions in children’s odds of living in unaffordable housing. Yet, for those in single-parent families, this protective association is largest among White children. For those in dual-parent families, this protective association is largest among Black children. Socioeconomic disadvantage and a greater propensity for three-generation families to reside in metropolitan areas with expensive housing appear to suppress the benefits emerging from multigenerational living.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".