Results from Lithuania’s 2018 Report Card on Physical Activity for Children and Youth
Bibliographic record
Abstract
The Global Matrix 3.0 "Report Card" assessment of physical activity was developed to achieve a better understanding of the global variability in child and youth physical activity. Lithuania joined the Global Matrix 3.0. The aim of this article is to summarize the results of the first Lithuanian Report Card, which included 10 indicators, as representative of individual behaviors, sources, and settings of influence indicators, and a health-related characteristic. The grades for each indicator were based on the best available Lithuanian data. The findings showed poor Overall Physical Activity, Active Transportation (C-), and Family and Peers (D). Sedentary behavior was graded C-, and Organized Sport Participation, Community and Environment, and Government were graded C. Physical Fitness and School indicators received the highest grade (C+). The first Lithuanian Report Card on Physical Activity of Children and Youth shows that Lithuanian children and youth have less than satisfactory levels of organized physical activity, active transportation to and from school, community and built environments, and government strategies and investments. The low levels of support from family and peers require more attention from health promoters. There is a gap in the evidence about active play that should be addressed by researchers and policy makers.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".