Anthropometric evaluations and assessment of school furniture design in Nigeria: A case study of secondary schools in rural area of Odeda, Nigeria
Bibliographic record
Abstract
This study was carried out on 621 schoolboys with age range of 12-17 years in Junior and Senior Secondary Schools in Odeda area of Odeda local government in Ogun State, Nigeria. Different anthropometric data were collected from these boys. It was observed from the results that all anthropometric dimensions of the school children increase with their age. Moreover, there exists a little difference between mean values of different anthropometric dimensions between the boys of 12-13 years (2.9% to 8.8%), 14-15 years (1.3% to 9.9%), and 16-17 years (1.4% to 5.5%). But the said differences become much higher (16.2% to 42.4%) when the same were compared between the children of 12 years and 17 years. Therefore, it can be said that the design of furniture for the children of 12 years will not match the children of 17 years. If single furniture is designed by considering dimensions of the children from 12 years to 17years, it will also not suit the children of all age groups. Therefore, in the present investigation, all the students have been divided into three combined age groups, e.g., 12-13 years, 14-15 years, and 16-17 years, and the percentile values (5 th , 50 th and 95 th ) of anthropometric measures, which will be helpful for designing of the classroom furniture.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".