Results from the Healthy Active Kids South Africa 2018 Report Card
Bibliographic record
Abstract
Background. Healthy Active Kids South Africa (HAKSA) Report Cards were produced in 2007, 2010, 2014 and 2016. Objective. The 2018 Report Card aims to report on the latest available evidence relating to the physical activity (PA), nutrition and body composition of South African (SA) children and adolescents. Methods. A review was conducted using the following databases: PubMed; Africa Journals Online; and Africa-Wide (EBSCOhost). Articles published from January 2016 to September 2018 were included for review by the HAKSA scientific advisory group. Data were extracted, and a grade for each indicator was assigned based on the available evidence and the consensus of the scientific advisory group. This included 12 PA indicators, 6 nutrition indicators and 3 body composition indicators. Results. There was no evidence of a significant change in any of the indicators since the 2016 Report Card. Grades for certain indicators have been downgraded (from 2016) to bring these to the attention of relevant stakeholders and industry. These include food insecurity and grades that relate to the implementation of policy on PA and nutrition in the school environment, and on advertising and media relating to nutrition. Conclusion. Key priorities for action include: safe opportunities for physical activity; minimising the gap between policy and implementation (school culture and environment, and government strategies); and the double burden of over- and undernutrition, which relates to the continuing concern about food insecurity in SA. There is a need for further research, including surveillance, on all indicators, for future Report Cards.
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 | 0.017 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.014 | 0.017 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.068 | 0.016 |
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".