Aristotle’s Theory of Deviance and Contemporary Symbolic Interactionist Scholarship: Learning from the Past, Extending the Present, and Engaging the Future
Bibliographic record
Abstract
Although his work has been largely overlooked by symbolic interactionists and other students of deviance, Aristotle (c384-322BCE) addresses community life, activity, agency, and persuasive interchange in ways that not only are remarkably consistent with contemporary symbolic interactionist approaches to deviance, but that also conceptually inform present day theories of deviance and provide valuable transhistorical comparison points for subsequent analysis. Following (1) a brief overview of an interactionist approach to the study of deviance, attention is given to (2) classical Greek conceptions of good and evil (especially as these are articulated by Plato) before turning more directly to (3) Aristotle’s notions of wrongdoing as this is reflected in his considerations of community, morality, agency, and culpability. While informed by Aristotle’s considerations of causality (as addressed in Physics and Metaphysics ), this statement builds most centrally on Aristotle’s Nicomachean Ethics and Rhetoric . Striving for a broader understanding of deviance as a humanly engaged feature of community life, the paper briefly compares Aristotle’s “theory of deviance” with Prus and Grills ( 2003 ) interactionist analysis of deviance. The paper (4) concludes with an assessment of the relative contributions of contemporary interactionist scholarship and Aristotle’s materials for the study of deviance as a community-engaged process.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.053 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".