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Record W4308117556 · doi:10.4102/ajod.v11i0.1089

Challenges and opportunities of centring the African voice in disability research

2022· article· en· W4308117556 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAfrican Journal of Disability · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsHealth Sciences Centre
Fundersnot available
KeywordsCentringCivilizationSociologyAction (physics)Inclusion (mineral)The RenaissanceDisability studiesRealisationSpace (punctuation)Allowance (engineering)Gender studiesPolitical scienceHistoryLinguisticsLawVisual artsEngineering

Abstract

fetched live from OpenAlex

In 2020, the African Network of Evidence to Action on Disability (also known as AFRINEAD) hosted its 10th conference in Cape Town. This paper synthesises inputs by the three authors as plenary addresses, particularly focusing on the challenges and opportunities of centring African voices in disability research. Our concern in this article is to engage with the question of exclusion as an issue not just in the everyday lives of people with disabilities but also in the world of ideas - the ideational space. We suggest that a reimagined disability study depends on the centring of African experiences, voices and knowledges. This is especially so as there are African concepts that are not rigorously pursued in research. African Renaissance thinking makes allowance not only for critically reflecting on the historical and contemporary constructs of disability but also for fashioning a higher civilisation in which people with disabilities can exist within society as worthy and valued human beings.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.282
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.007
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.258
GPT teacher head0.407
Teacher spread0.149 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it