A Legal Analysis of the Protection of the Rights of Persons with Disabilities During the COVID-19 Pandemic in Nigeria
Bibliographic record
Abstract
Abstract Persons with disabilities are often discriminated against in society on the basis and/or grounds such as race, ethnicity, cultural beliefs, as well as religious beliefs. Moreover, there is a general negative societal attitude and a negative perception against persons with disabilities globally. For instance, persons with disabilities are negatively treated as a charitable problem of the society in many countries, including Nigeria. This approach could have deliberately or inadvertently led to the omission of the specific rights of persons with disabilities from the list of fundamental rights under the Nigerian Constitution, 1999. However, the recent enactment of the Discrimination Against Persons with Disabilities (Prohibition) Act, 2018, could be a positive step in addressing numerous challenges such as poverty, unemployment, discrimination, and health care problems that are faced by persons with disabilities in Nigeria, especially in the wake of the novel coronavirus (COVID-19) pandemic. Against this background, the article discusses the challenges that are encountered by persons with disabilities in Nigeria during the COVID-19 pandemic. This is undertaken to, inter alia, assess the adequacy of the legal and constitutional protection on the rights of persons with disabilities, especially during the ongoing COVID-19 pandemic in Nigeria. Moreover, the flaws and gaps in the current legal and constitutional regime for the protection of the rights of persons with disabilities in Nigeria are discussed. Thereafter, possible recommendations to curb such flaws in Nigeria are provided.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".