Inclusive education for sustainable development: Examining the Inclusive Education Policy of the Gambia 2016-2030 in attaining economic progress through creating Human Capital
Bibliographic record
Abstract
Education as a fundamental right is a key player in the drive for economic posterity. It is widely seen as an essential foundation for sustainable development, which could serve as an agent for economic growth, societal progress and environmental sustainability. It is against this backdrop, that the national education policy 2016-2030 was formulated to transform the Gambia into an economically sustainable country. It is a focus of global attention because for societies to thrive, education should take centre stage where individuals regardless of their physical ability or economic status will be productive persons. However, as people possess different abilities in different ways, the attention of advocates across the world has called for justice within the education setting, advocating for the right of every individual to access education in a conducive environment free from all forms of discrimination. This study aims to examine the national education policy in enhancing inclusive education policy for economic growth and sustainable development. The qualitative study conducted semi-structured interviews to assess the progress of the policy in attaining economic growth amongst the youth, inclusion of persons with disabilities and its challenges. The results show that the policy has improved in terms of human capital development and mainstreaming of special needs children. However, there are challenges like unequal distribution of state funds amongst schools and special needs children not being given full attention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".