From Total Institution to Status Bloodbath: Goff man as a Comparative Researcher and Grounded Theorist
Bibliographic record
Abstract
Erving Goff man has not only had a huge impact upon his home discipline of sociology but may be its most cited, as well as best known member ever. Nevertheless, Goff man continues to be heavily criticized by his fellow sociologists for his allegedly undecipherable and sloppy methods for conducting empirical research and constructing and accumulating general theory. We demonstrate here that while some of his specific practices were intuitive and unorthodox, and perhaps not always available to Goff man himself through self-reflection, they often included systematic empirical comparisons and generalizations, and grounded, general theory. It is tragic that he apparently died lamenting that these common characteristics of his work have been so little recognized (Berger 1986). He encouraged Verhoeven (1993), among others, to rectify this, and hopefully our own eff orts here have contributed to this important, but unfinished business.
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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 | 0.027 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.011 | 0.068 |
| Scholarly communication | 0.011 | 0.018 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.007 |
| 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".