The Use of a Nonrefundable Tax Credit to Increase Children’s Participation in Physical Activity in Alberta, Canada
Bibliographic record
Abstract
BACKGROUND: Potential income disparities were examined in the (1) awareness and uptake of the Children's Fitness Tax Credit (CFTC), and (2) physical activity (PA) of children from families who did and did not claim the credit in Alberta, Canada in 2012 and 2014. METHODS: Secondary analyses of 3 cross-sectional data sets of grade 5 students (10-11 y) were performed, including Alberta Project Promoting healthy Living for Everyone Schools 2012 (N = 1037), and Raising healthy Eating and Active Living Kids Alberta 2012 (N = 2676), and 2014 (N = 3125). Parents reported whether they claimed the CFTC in the previous year, their education and household income, and their child's gender and PA. Children self-reported their PA from the previous 7 days. In Alberta Project Promoting healthy Living for Everyone Schools, children also wore pedometers. Analyses adjusted for clustering within schools and demographic factors. RESULTS: Higher income families (≥$50,000/y) were more likely to be aware of and to have claimed the CFTC compared with low-income families (<$50,000/y). The CFTC was associated with organized PA with larger associations for higher-income families (odds ratio = 9.03-9.32, Ps < .001) compared with lower-income families (odds ratio = 3.27-4.05, Ps < .01). No associations existed for overall PA or pedometer steps with the CFTC. CONCLUSIONS: Income disparities exist in the awareness, uptake, and potential impact of the CFTC. Tax credits are not effective in promoting overall PA.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".