Bibliographic record
Abstract
Political Emotions: Aristotle and the Symphony of Reason and Emotion, Marlene K. Sokolon, DeKalb: Northern Illinois University Press, 2006, pp. 217. Marlene K. Sokolon has provided an intellectually stimulating and highly original work on Aristotle's understanding of the emotions, mainly as presented in his treatise the Art of Rhetoric. The central thesis of Sokolon's book manifests itself in her analysis of the emotion of anger. According to Sokolon, for Aristotle anger is the paradigmatic human emotion, defined as the desire for revenge for a dishonourable and undeserving public insult against oneself or those one loves. Of this desire for revenge, Sokolon argues that “for Aristotle, unique human anger is not ‘at’ something, but more properly ‘with’ what some other person did or intends to do. Anger and the other political emotions are certain kinds of judgments or perceptions about sociopolitical circumstances. Anger judges specific kinds of events with an acknowledged political, or what we now call ‘cultural,’ meaning” (p. 55). Thus, Sokolon argues that for Aristotle the emotional experience of anger occurs in social and political contexts where there are evaluations of worth in situations involving relations of power. But if anger is the paradigmatic human emotion, this means that anger is not simply representative of various political emotions, but illustrates that human emotion as such is an essentially political phenomenon. Sokolon's thesis, therefore, is that for Aristotle, “man is by nature a political animal” not simply because he possesses reason, the apparent claim of the Politics, but also because he experiences emotions.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.030 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".