Information and Knowledge Transfer in the rural community of Macha, Zambia
Bibliographic record
Abstract
Science is using methodologies to study behaviour. These methodologies are socially constructed, culture specific, and deeply affected by North American and Western language. African cultures feature empathic processes fueled by compassion and the desire for co-existence. It operates on communal, often primary oral, cultures and uses mostly oral tradition in its presentations. Oral traditions process knowledge and verbalize data specifically.This case of long term research in which Information and Communications Technology is introduced in a highly oral and rural culture shows that using constructs available in primary oral culture can create outcomes that are a useful function within oral tradition circumstances. Analysis of methodologies used during the eleven-year case study suggest that outcomes benefit from interactions that are aligned within oral-culture formats. The case study follows 'the flow of science' - analysing, interpreting, clarifying, constructing - primarily in the oral tradition. Outcomes appear fruitful in oral traditions.This long term and unique approach opens the door to new ways of understanding in rural Africa, and recognition that literacy and orality exist side by side.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".