Tradition, Transnational Connections, and Teaching through Sunjata’s Story
Bibliographic record
Abstract
This article presents an interview with Hawa Kassé Mady Diabaté, Lassana Diabaté, and Chérif Keita - a conversation facilitated by Ely Lyonblum, at the time a Research Assistant with Marcia Ostashewski at Cape Breton University’s for the Singing Storytellers Symposium. Hawa Kassé Mady Diabaté is a jalimuso (female griot) who descends from a prestigious lineage of oral performers and wordsmiths from the village of Kéla in Southern Mali. Lassana Diabaté is a balafon player originally from Republic of Guinea who moved to Mali at a young age and is recognized as one of the best players of jali bala (the balafon of the Mande griots). Jali/Djeli and jalimuso often learn techniques and repertoire through extended familial networks of musicians within Mande society that often cross national boundaries. The two musicians discuss their musical upbringings, the importance of epics like the Sunjata Fasa in Mande culture, and the effect that new technologies have on musical performance and historical narrative. Chérif Keita acted as translator for the interview and provides an introduction to this article.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.013 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".