Non-modern Africa and modern non-Africa: Intertextual discourse about who we are and where we came from
Bibliographic record
Abstract
The idiom no man is an island might be rewritten as no text is an island, meaning that no text exists in literary isolation and that every piece of writing instead belongs to a landscape of others. References, endnotes, footnotes, bibliographies, and the use of phrase, term, or defi nition will situate a text within a discursive network of understandings, theories, paradigms, and genres. Intertextual discourses about the origins of humanity often cross generic boundaries between religion, science, informative media and entertaining fi ction through the sharing and borrowing of words and concepts. These genres, however reluctantly, inevitably engage with one another in what emerges as a single discourse about who we are and where we came from. Throughout this discourse, certain concepts have formed as time, place, and identity are linguistically associated with one another. The dichotomy of Non-Modern Africa as Other and ModernNon-Africa as Self is one such concept. Caution must be exercised by researchers who wish to talk about human origins, as these types of concepts may have very real implications in political, economic, social, and cultural arenas.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.027 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".