Investigation of the Awareness and Habits of Secondary School Students about Cleanliness and Hygiene from Various Variables
Bibliographic record
Abstract
Cleanliness, hygiene and personal hygiene habits have an extremely important place in maintaining and developing an individual’s physical and spiritual health. In contrast, it has been observed that research on student behaviour for cleaning and hygiene applications has been limited in the literature. In this case, “What are the cleaning and hygiene habits of students?” It has emerged as a necessity to answer the question. In this study, mixed blending method has been used. The study group consisted of 1300 students, studying in 12 different secondary schools in the city of Kars. In order to collect data, personal information form, “Personal Cleansing and Hygiene Habits Scale” developed by the researcher and open-ended questions were used. It was observed that the general cleaning and hygiene levels of the students were not statistically significantly different according to gender variables (p>.05). In terms of the personal hygiene and hygiene habits of the students’ significant differences have been found according to their parents’ education status, the number of individuals in their families and the level of their education. Significant differences have been found in terms of the personal hygiene and hygiene habits of the students according to their parents’ education status, the number of individuals in their families and the level of their education (p
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".