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Record W2939466579 · doi:10.1017/s1060150319000068

Having It Both Ways with Erving Goffman

2019· article· en· W2939466579 on OpenAlexaboutno aff
John Plotz

Bibliographic record

VenueVictorian Literature and Culture · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCross-Cultural and Social Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSociologyEthnographyReading (process)Presentation (obstetrics)PsychoanalysisPeriod (music)Identity (music)Media studiesGender studiesPsychologyAestheticsAnthropologyArtLaw

Abstract

fetched live from OpenAlex

Historians of social science from Anthony Giddens forward have ably chronicled Erving Goffman's legacy. Goffman's resonant book titles alone hint at the Dickensian acuity of his social close-reading: The Presentation of Self in Everyday Life (1956), Behavior in Public Places (1963), Interaction Ritual (1967), Frame Analysis: An Essay on the Organization of Experience (1974), and Forms of Talk (1981). I envy newcomers the opportunity to read pieces like “On Cooling the Mark Out” (1952) and “Where the Action Is” (1967) with fresh eyes. Goffman, born in 1922 in Alberta, Canada, to Ukrainian parents, attended the University of Manitoba and the University of Toronto before receiving a PhD in sociology from Chicago. His fieldwork was in the Shetlands, and Asylums: Essays on the Condition of the Social Situation of Mental Patients and Other Inmates (1961) and Stigma: Notes on the Management of Spoiled Identity (1963) were both written after a period of ethnographic immersion at St. Elizabeth's mental hospital in Washington, DC. It may help first-time readers to know that as an adolescent he had a “special aptitude for noticing details of people's interpersonal conduct”; also that “his Chicago classmates nicknamed him ‘the little dagger’ because of his talent for the pointed personal comment. Sometimes, they felt, he never knew when to stop.”

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0080.015
Scholarly communication0.0070.010
Open science0.0010.004
Research integrity0.0050.013
Insufficient payload (model declined to judge)0.0080.004

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.

Opus teacher head0.007
GPT teacher head0.251
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

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