Translating the Universal Declaration of Human Rights into Practice
Bibliographic record
Abstract
The United Nations (UN) has adopted the Universal Declaration of Human Rights (UDHR) to ensure that its member states promote and respect human rights. One of these rights is the right to security. There are studies that have been conducted about the right to security of teachers and learners; however, less is known about the translation of the UDHR security provision into practice to ensure the security of teachers in South African public schools. This qualitative study intended to close this gap by responding to the following research question: How is the UDHR translated into practice to ensure the security of teachers in South African public schools? The purpose of this article is to establish a human rights-based foundation for state support for ensuring teachers’ right to security in public schools. To answer the research question and achieve the purpose of this article, data were sourced from South African education law and national policy sources, Department of Basic Education (DBE) reports, research reports and academic articles that focus on the security of teachers. Critical policy analysis was used as both a theory and a method in this study. This approach involved examining various discourses and power relations that take place through the construction and functions of policy. The study provides two main findings. These findings are: (i) National law and policies align internationally, but some school-based safety policies fall short (ii) There is a difference between policy rhetoric and practiced reality on teacher security in South African public schools. It is recommended that despite the DBE’s efforts to ensure teachers’ security in public schools, the translation of the UDHR security provision into practice should be improved and impactful. This study contributes to the field of education law and policy, and it sheds light on how the UDHR provisions are translated into practice.
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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 | 0.128 | 0.139 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.008 | 0.051 |
| Scholarly communication | 0.014 | 0.020 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.007 | 0.012 |
| 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".