Consumption within a soft total institution: Discursive inculcation in the Tablighi Jamaat
Bibliographic record
Abstract
Abstract Erving Goffman’s concept of total institutions has been seldom explored in terms of how it restricts or promotes consumption practices. In an effort to redress the lacuna in the extant literature, this article draws on the findings of an ethnographic study of the Tablighi Jamaat, an orthodox religious organization originating in South Asia, whose participants undergo discursive inculcation in an environment that may be characterized as a soft total institution. We explore how consumption in such an environment entails processes of traditionalization under (late) modernity. Our findings show that consumption in a soft total institution requires subjects to monitor their own behavior discursively in order to attain certain intended, spiritual objectives. The study has implications for how consumption can be a means by which to either meet or inhibit life goals. In terms of theoretical contribution, this article begins to demarcate the boundary conditions between Goffman’s total institution and, what we are terming here, a soft total institution. Finally, we further Goffman’s original thesis by describing some of the subjects’ thoughts and experiences of their daily lives after their inculcation within the institutionalized setting.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".