Investigating how high school deaf students spend their leisure time
Bibliographic record
Abstract
This paper presents an investigation on deaf students' interests in spending their leisure times.We design a questionnaire and distribute among all deaf students who are enrolled in high schools in two provinces of Iran.The questionnaire consists of three parts, in the first part, we ask female and male deaf students about their interests in various entertainment activities in Likert scale.In terms of gender, we find out that walking inside or outside house is number one favorite exercise for female students while male students mostly prefer to walk on the streets.Although male students prefer to go biking or running activities, female students prefer to go for picnic or similar activities.This could be due to limitations on female for running or biking inside cities.While going to picnic with members of family or friends is the third popular activity for male students, stretching exercises is third most popular activity among female students.Breathing exercise is the fourth most popular activity among both male and female students.The second part of the survey is associated with the barriers for having no exercise among deaf students.According to our survey, while lack of good attention from public and ordinary people on exercising deaf students is believed to be number one barrier among male students, female students blame lack of transportation facilities as the most important barrier.However, both female and male students believe these two items are the most important factors preventing them to exercise.Lack of awareness for exercising deaf students and lack of good recreational facilities are the third most important barriers among male and female students.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".