Socioeconomic differences in parental financial support, coresidence, and advice: A portrait of undergraduate students in the Canadian Prairies
Bibliographic record
Abstract
In this paper, we examine the intersections of parental support and family socioeconomic background within an undergraduate sample (N = 596) in a mid-sized Canadian Prairie city. Coresidence, financial support, and parental and professional financial advice are examined as types of 'family capital' that may be distributed unequally across socioeconomic groups. In keeping with previous literature, findings showed that students whose parents had university education and higher incomes received more robust coverage of their housing and school expenses. Students whose parents were university-educated were also more likely to be living with a parent, though no relationship was found between parental income and coresidence. Contrasting with previous literature, few relationships were found between socioeconomic background and receipt or influence of financial advice. These results contribute to the literature by generalising claims about family capital to a Canadian student sample, where relatively few studies have empirically examined intergenerational transfers as mechanisms for transmitting privilege during the transition to adulthood. With increasing demands for higher education and simultaneous declines in government subsidisation of its costs, disparate access to family capital is likely to intensify the reproduction of social inequality across generations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".