Sankofa: towards African-centred research methodological framework
Bibliographic record
Abstract
This article presents critical duo-ethnographic reflections on our experiences as Western-trained researchers conducting research in Ghana. We propose Sankofa as a methodological framework to envision possibilities for decolonizing and indigenizing research. As a methodological framework, Sankofa provides a critical paradigm for both African and non-African researchers to learn, unlearn, and relearn authentic and culturally sensitive modes of researching and mobilizing knowledge. Sankofa offers critical decolonial reflexivity in the research process by guiding researchers and participants to reflect on and learn from the histories of the past to reimagine a decolonial future. Our duo-ethnographic reflections reveal challenges, including navigating institutional ethics, respecting communal practices, and confronting power imbalances embedded in traditional research paradigms. The application of Sankofa shows promising outcomes in addressing these challenges and enabling a research process that honors African Indigenous knowledge, fosters authentic and ethical accountability and communal empowerment.
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 | 0.077 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".