People of Determination (Disabilities) Recruitment Model Based on Blockchain and Smart Contract Technology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Blockchain technology is an innovative technology that has grown in prominence in recent years that will certainly regulate the development of our network society in the upcoming future. Blockchain technology has received increased care and interest from both academic and general practitioners across the world. Various research articles have been written on the approach, how blockchain technology works and its possible applications in different industries, governmental authorities, etc. Nevertheless, there are no conducted studies that have focused on the usage of blockchain technology in the recruitment process of people of determination (disabilities). This paper aims to establish a POD (People of Determination) platform model. The aim of the model is to support the recruitment process of people of determination (disabilities) by enhancing the chances of them who were hired in different types of United Arab Emirates organizations. To the best of our knowledge, no previous research has been conducted on the usage of blockchain technology in recruitment process of people of determination (disabilities). This research paper will therefore aim to contribute to the existing literature about blockchain technology and recruitment process by providing a proposed model on how to implement the process.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it