Earthquake Controversies, the L’Aquila Trials, and the Argumentative Struggles for both Cultural and Scientific Power
Bibliographic record
Abstract
This article extends the work of researchers from the rhetoric of science and science and technology studies communities, and interprets the communicative aftershocks of the 2009 L’Aquila earthquake. The authors argue that some of the scientists belonging to the Italian Serious Risk Commission ended up being charged with manslaughter, and, at various times during this controversy, provided publics with different ways of assessing aleatory and epistemic risk. While the defendants originally inflated their ethos to quell concerns about earthquake predictions that came from a technician named Giuliani, they later dismantled some of their own authority in sociotechnical ways once they appeared in court.
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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 | 0.030 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.021 | 0.070 |
| Scholarly communication | 0.015 | 0.018 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.016 | 0.013 |
| Insufficient payload (model declined to judge) | 0.005 | 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".