Doing Disability Research in the Majority World:an Alternative Framework and the Quest for Decolonising Methods
Bibliographic record
Abstract
Research on disability in the so-called majority world remains scarce, and that which exists, continues to be dominated by Western epistemologies and methods, transferred indiscriminately from the global North to the global South. Unfortunately, the cultural and contextual relevance of these approaches remain largely unquestioned, a dynamic premised on the assumption that theories and methods bred in Western spaces are not only superior but applicable to all and sundry. This is what we term the neocolonisation of research. In order to challenge this, our paper takes up Tuhiwai Smith’s (1999) call for decolonizing research, by exploring the potential for a conceptual framework blending elements from poststructuralism, post and neo-colonialism, and Hardt and Negri’s (2000) work on Empire to engage more meaningfully with the study of disability across global contexts.
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How this classification was reachedexpand
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 | 0.033 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".