Of Bonfires, Mindsets, and Policies
Bibliographic record
Abstract
Abstract The notion that archives are neutral places with no vested interests has been undermined by current philosophical and theoretical handlings of the concept of the ‘Archive’; it is now undeniable that archives are spaces of power, with the power to include and exclude, to distort, omit, and silence voices (Carter, 2006: 216). Inevitably, ‘not every story is told’. In the African context, this concern is pressing, considering the varied and sometimes ephemeral ways in which ‘texts’—written, visual, oral, ritual, performative—are documented. However, beyond the concern for the gaps created by the omission or ignoring of these non-conventional archives in African archival work, there yet remains within the conventional practice of archival management on the African continent, a simmering mix of factors that create silences. This chapter examines this multi-causal matrix of silence from the Ghanaian perspective.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.041 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".