Clothing purchase behavior and the Canadian household life cycle
Bibliographic record
Abstract
The first intention of this research is to test if Wells and Gubar's model (1966) of consumer behavior, based on the life cycle, still explains the Canadian population's consumption behavior. A second objective, if warranted, is to determine the possibility to segment the Canadian population based on life cycles with the aim of explaining garment/apparel consumption. Using the Survey of Household Spending from Statistics Canada (2009), this article analyses total clothing expenditures and their subcategories of expenses for women and girls, men and boys, and children. Each expense is analyzed using two different data: (1) gross amount of money spent annually and (2) percentage of the category on household total spending. The three hypotheses of this research are validated, confirming (H1) the non-representativeness of Wells and Gubar's model; (H2) the importance of integrating single households in the life-cycle model since their purchase behaviors are significantly different from those of traditional households; (H3) the possibility to segment based on life-cycle criteria to better understand Canadian realities.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".