Erving Goffman’s View of “Deviance”: “Self” and “Society” as the Sources of Deviancy and Conformity
Bibliographic record
Abstract
Not much has been written about Erving Goffman’s conception of “deviance”. The little that exists often mistakenly reduces it either to what I refer to in this paper as “Stigma and Mental Illness”, or diminishes its novelty by rendering it a variant of “interactionist” view of deviance. The argument of this paper is that he had a broader and novel conception of deviance. In fact, he distinguished between six interrelated types of deviance: (1) Deviance related to presentation of “self” in social interactions; (2) Deviance as lack of self-control and violation of interactional scripts; (3) Deviation from assigned social roles in the system of social stratification; (4) Social deviance, i.e., willful and unabashed violation of social order; (5) Deviation from “identity values”; (6) Deviation due to a search for excitement
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.033 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 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".