Designing afro-emancipatory qualitative research with and for Black people
Bibliographic record
Abstract
Since the tragic death of George Floyd in May 2020, there has been increased interest in anti-racist research. Consequently, several scholars are instigating qualitative inquiries in Black communities with limited preparation or expertise. This article presents a reflection regarding essential principles that can guide general and afro-emancipatory health and social sciences qualitative inquiries in Black diasporas. We contend that it is essential that researchers engage in reflexivity and consider Black ontologies, axiology and epistemologies. Furthermore, we propose the application of the following deontological principles to fulfil an ethical afro-emancipatory research framework: (a) include critical theories, (b) target the liberation of Afro-descendant peoples to enable their full participation as their whole selves in society; (c) ensure their leadership and meaningful involvement throughout the research process; (d) implement accountability mechanisms towards community members; (e) embrace intersectionality, an asset-based lens, and aspirational stance and; (f) foster healing, growth and joy.
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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 | 0.240 | 0.146 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.018 | 0.019 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier 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".