Make Room for Play: An Evaluation of a Campaign Promoting Active Play
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the context of rising screen time, only a third of Canadian children are achieving adequate amounts of active play, an important source of physical activity. ParticipACTION, a national not-for-profit organization, created the "Make Room for Play" campaign targeting parents with television advertisements depicting how screen time takes away from active play. The advertisements featured children engaging in active play (e.g., jump rope) while a black screen progressively sequesters the room for them to play. This study's purpose was to evaluate the campaign using the hierarchy of effects model, a framework for conceptualizing the impact of mass media campaigns. It was hypothesized that recall would relate to intermediate (e.g., cognitions, self-efficacy) and distal (e.g., parental support) factors. Twenty-six percent of the general population and caregiver samples surveyed (N = 1576) recalled (unaided) the advertisement and 45.9% recalled when prompted. Parental support was significantly higher in those recalling the campaign, p = .009. Twenty-four percent of parents reporting unaided recall (versus 14.0% of those not) tried to engage in active play with their children and 21.2% (versus 12.0%) tried to create opportunities for children to engage in play. Strengths and limitations of mass media approaches targeting active play and screen time are discussed.
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.
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it