Bibliographic record
Abstract
Abstract Focus of Presentation Searching on documents about High School (or Secondary) education we found some differences in both curriculum, Brazil and Canada. High School in Brazil has three year (grade 10 to 12). In other hand, High School in Canada has four years (grade 9 to 12). The main focus of this work is a comparison about how “health promotion” appears in High School curriculum in Brazil and Ontario-CA, in especial at Physical Education curriculum. Findings In Brazilian High School, Physical Education curriculum is mandatory. However the key-words “health” appears 11 times in a federal document (Ministry of Education) with 241 pages. Key-words like “health promotion” appear one time and “social determinants” none. Ontario-CA have a Health and Physical Education curriculum. In this case, the key-words “health” appears more than 1000 times in a province document (Ministry of Education) with 224 pages. Key-words like “health promotion” appear 14 times and “social determinants” 3 times. Conclusions/Implications Text Physical Education curriculum in Brazil need to emphasize “health promotion” contents as a life condition and physical literacy and health literacy. Meantime, Ontario-CA curriculum show a few content about “social determinants” which is a core concept in “health promotion” studies. Key messages Text High School curriculum need emphasize “health promotion” and “social determinants” as a core concept for a physical literacy and health literacy.
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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".