16. Obesity Surveillance: An Investigation of Health Policy and Programs in Ontario
Bibliographic record
Abstract
Today, childhood obesity is one of the most important challenges our society faces. The objective of this research project is to contribute to ongoing academic discussions of how to address issues of childhood obesity. To accomplish this goal, this project investigates the historical development of policies and educational programs regarding childhood obesity issued by the government of Ontario and Halton District School Board. In particular, this project explores the following questions: 1) Is there evidence of childhood obesity in Ontario and/or the Halton region? 2) What educational programs, policies, or action plans has the Ontario government and Halton District School Board established to target childhood obesity? 3) Are existing policies, educational programs, and action plans of health promotion considering children as a vulnerable population thereby maintaining a safe environment for children? Specifically, this project speaks to policy makers and educators by examining the risks and social impacts of policies and programs. For example past surveillance techniques created to collect statistics of childhood obesity, develop policies, and evaluate educational programs have been criticized for scrutinizing persons through a process of monitoring, analyzing, and comparing (Rich 2010) as well as breaching persons’ rights to privacy (Haggerty and Ericson 2000). Overall this project will contribute to ongoing academic discussions regarding how best to address childhood obesity because evidence drawn from past policies, educational programs and action plans can be used to develop more effective means of impacting childhood obesity while also being mindful of the potential risks of surveillance based educational programs.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".