Analysis of Self Efficacy-Sufficiency Levels of Individuals with Visual Impairment According to Some Variables
Bibliographic record
Abstract
This study was conducted with the aim of determining self efficacy-sufficiency levels of visually impaired individuals according to some variables. Bandura (1994) states that self-sufficiency, defined as an individual’s belief on operating a specific job, is an important factor for the athletes. Self-sufficiency results in choosing a field of study voluntarily, feeling a high motivation for accomplishing that job, endeavoring and spending time on the study. Self-sufficiency is about the individual’s specific area or behavior group (Akkoyunlu & Orhan, 2003). The study was conducted on 127 male and 60 female visually-impaired individuals, a total of 187, with different visual acuity in different visually-handicapped clubs. The voluntary basis was taken into consideration in participation. As the data collection tool, “Personal Information Form” and “Self-Efficacy–Sufficiency Scale” which was developed by Sherer et al. (1982), and adopted into Turkish by Gözüm and Aksayan (1999). The data set was analyzed in SPSS 20.0 packaged programme. The data was purified from loss and wrong coding, and the normality hypothesis was done with kurtosis and skewness values. In the analysis of the data, frequency, the average standard deviation was used; besides, T-Test (in paired comparisons) gender, disability status, marital status and branches of sports; one-way variance (ANOVA) test in age, level of education, level of income and visual acuity were used. When one-way ANOVA results of self-sufficiency scores according to gender, age, disability status, level of education, level of income, and visual acuity were analyzed, it was stated that there was a significant difference (p0,05). When evaluated the information above, it can be said that like self efficacy-sufficiency concept can be in different levels and different dimension in different areas of life; it is effective on visually-impaired individuals. In this respect, it is considered that this study will open a new window to this area and contribute to the visually-impaired athletes. Besides, it is suggested that a new study on how self efficacy-sufficiency concept is in the visually-impaired athletes and other individuals, and evaluation of how they are affected. In this concept, the general aim of this study is to analyze the levels of self efficacy-sufficiency of visually-impaired athletes.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".