Civic amnesia and legal memory: to remember and forget in the lawcourts
Bibliographic record
Abstract
There is a temporality particular to each type of rhetoric: to deliberative oratory the future, since it gives advice, pro or con, concerning what will happen; to forensic oratory the past, since both prosecution and defense always speak about events that have happened; and to epideictic oratory the present, since all speakers issue praise or blame according to existing conditions, though they often also recall the past and anticipate the future. Aristotle Rhetoric 1358b13–20 What if banning memory had no other consequences than to accentuate a hyperbolized, though fixed, memory? Loraux 2002: 261 ATHENS' AMNESTY AND LAW'S ALĒTHEIA Forensic oratory, as Aristotle notes, is oriented toward the past. The law can try only events that have already happened. The speaker of Isocrates 20 bemoans this limitation. It would be best, he says, if criminals bore some mark ( sēmeion ) that enabled us to punish them before they committed their crime, “inasmuch as it is better to find a means of averting future problems than to punish those that have already occurred” (12). As it is, one should consider it a windfall when a criminal does come before the court, and punish him before he does something worse (12–14). Inherently retrospective, dikē is associated in Greek thought with memory. Zeus “does not overlook (or “forget,” lēthei ) that sort of justice that a city holds in it,” says Hesiod ( Erga 268–69). The avenging spirit of the murder victim, a demonic agent of justice, is called the alastōr , literally the “unforgetting one.”
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".