An examination of willingness to participate and willingness to pay for a universal school food program in the Canadian context
Bibliographic record
Abstract
OBJECTIVE: To examine parents'/caregivers' willingness to participate and willingness to pay (WTP) for a cost-shared school food program (SFP) and its associated factors. DESIGN: A quantitative survey design was used where WTP for a hypothetical SFP was elicited using a double-bounded dichotomous choice elicitation method. We used a double hurdle (logistic and truncated regression) model to examine WTP and positively or negatively associated factors. SETTING: Saskatoon Public School Division elementary schools situated in high-, mid- or low-median-income neighbourhoods. PARTICIPANTS: Parents or caregivers of children attending grades 1 to grade 8 in the Saskatoon Public School Division elementary schools. RESULTS: 94 % respondents were willing to participate in a SFP while less than two-thirds of participants were willing to pay for such a program. Over 90 % respondents from all the socio-economic groups were willing to participate. Multiple household income earners, higher household income, higher number of children, household food security status and higher academic attainment of parents'/caregivers predicted greater willingness to pay. Mean willingness to pay was $4·68 (CAN), and households reporting moderate or severe food insecurity were likely to be willing to pay significantly less for a SFP. CONCLUSION: A cost-shared program might be financially sustainable in Canada if community characteristics such as household food insecurity status, economic participation of women and average household size are kept in mind while determining the price of the program.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 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".