Erving Goffman: vida y genealogía intelectual
Bibliographic record
Abstract
What does happen when two or more persons are in a face to face situation? How the interaction develops when one of them commits an infamy, presents a physical disability or if he is considered as a mental patient? Erving Goffman (1922-1982), of Canadian origin, has tried to answer to this type of questions along his research life. It result an abundant, exciting but also controversial work because if some analysts see in Goffman the principal sociologist of the second half of the 20th century, others think that his analyses only constitute the reflection of a «petit bourgeois» point of view on the urban American society. This article presents both the life and the intellectual genealogy of this sociologist. ¿Qué sucede cuando dos o más personas se encuentran en una situación de cara a cara? ¿Cómo se desarrolla la interacción cuando una de ellas comete una torpeza o presenta una discapacidad física o si está considerada como una enferma mental? Erving Goffman (1922-1982), de origen canadiense, ha intentado contestar a ese tipo de preguntas a lo largo de su vida investigadora. Resulta de todo ello una obra abundante, apasionante pero también controvertida, puesto que algunos analistas ven en Goffman el mayor sociólogo de la segunda mitad del siglo XX mientras que otros consideran que sus análisis solo constituyen el reflejo de un punto de vista «pequeño-burgués» sobre la sociedad urbana americana. Este artículo presenta tanto la vida como la genealogía intelectual de ese sociólogo.
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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 | 0.003 |
| 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 | 0.019 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".