The Attitudes of the Holy Land Institute for the Deaf-Salt, Jordan towards Deaf Socially and Educationally
Bibliographic record
Abstract
The study aimed to recognize the attitudes of the Holy Land Institute for the Deaf-Salt, Jordan towards Deaf Socially and Educationally in the academic year 2016-2017, which consists of instructional and vocational staff towards deaf socially and educationally according to some variables (gender, age, the level of education). The sample of the study included staff members of the institution. The researchers used the Third Likert-Type and the descriptive approach. The sample of the study consisted of 69 persons whose answers achieved the required conditions. The results showed a decrease in the negative attitudes level, which reflected high positive attitudes according to the treatment of the study sample with deaf socially and educationally. Results also showed no significant differences refer to gender and age due to the attitudes. But there were significant differences due to the educational level of the workers in this institution giving advantage to the academic certificate and over, which means there were huge effects to the academic level in the social and educational attitudes towards the deaf.The study recommended the importance of spreading and increasing the level of awareness among the people who work in this institute to the local society about how to cope with positive social and educational attitudes in order to increase the level of the deaf adaption and spread the culture of respecting the categories.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".