Canadian Consumer Financial Vulnerability, Stress, and Well-Being
Bibliographic record
Abstract
Le présent article soutient que les indicateurs expérientiels de la vulnérabilité financière permettent d’avoir une compréhension plus solide du phénomène que les mesures couramment utilisées pour évaluer l’endettement des ménages canadiens. Les résultats de l’enquête sur le bien-être financier de 2018 de l’Agence de la consommation en matière financière du Canada (ACFC) révèlent que la vulnérabilité financière est multidimensionnelle, qu’elle est fortement liée à un faible revenu ainsi qu’à des chocs négatifs sur le revenu et les dépenses. D’importantes variations dans d’autres facteurs potentiels sont évidentes, notamment le fait que les personnes financièrement vulnérables dans des dimensions objectives ne déclarent pas se sentir stressées et vice versa. L’étude conclut qu’une telle représentation nuancée de la vulnérabilité financière s’avère particulièrement prometteuse pour évaluer pleinement l’efficacité des politiques et inspirer des interventions mieux éclairées.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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; both teacher heads agree on what is shown here.
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".