Develop a List to Detect the Professional Tendencies of Hearing Impaired Enrolled in Vocational Rehabilitation Programs and Deaf Schools in Jordan
Bibliographic record
Abstract
The current study aimed to develop a list of professional tendencies and verify the implications of its validity and reliability and know the professional tendencies and impact of gender variables and the degree of disability on hearing-impaired people's professional tendencies. To achieve the objectives of the study, the researcher developed the list of Arabized professional tendencies of John Holland in a way that suits the characteristics of the hearing-impaired and using the previous literature and previous studies, where the indications of validity and reliability were extracted from the pilot study, then the study tool was applied to the final sample, which consisted of (118) hearing-impaired individuals from deaf schools and vocational rehabilitation centers in Jordan who are in the stage of professional selection in cooperation with my translators of sign language of schools and rehabilitation centers, where the study reached the indications of validity and reliability of the study tool, the study also found that there was no effect of gender and degree of disability variable on the professional tendencies of hearing-impaired people, as it came out with a set of research and educational recommendations.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".