Bibliographic record
Abstract
In this paper, I examine how the Ogoni use demonstrations, boycotts, petitions, etc, as counter-narrative forms possessing “a formative energy in the dynamic of history” (Sfez: 1999, Colin Caret: 2003). Since demonstrations and protest marches help to collectivize the people and serve to canalize diverse oppositional sentiments, I will interpret these forms as elemental sites of popular sovereignty. Further, since the law is frequently used by the Nigerian state to legitimize and naturalize its repression of minority communities, I examine how dissenting groups transgress and de-legalize the law in their pursuit of a more egalitarian modernity. Throughout this paper, I use what I shall term the aesthetics of spectacle - a cardinal tenet of the theatre, as the main interpretive idiom to examine how Ogoni communal refusal is mobilized against a national and transnational technology of oppression.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.022 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".