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Record W1538351187 · doi:10.18533/journal.v3i8.527

Machines, People, and Social Interaction in “Third-Wave” Coffeehouses

2014· article· en· W1538351187 on OpenAlexaff
John Manzo

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicItalian Fascism and Post-war Society
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSocialitySociologyEmpirical researchConsumption (sociology)Product (mathematics)Focus (optics)Face (sociological concept)Focus groupSocial relationPublic relationsInternet privacyMedia studiesComputer scienceSocial scienceEpistemologyPolitical scienceAnthropology

Abstract

fetched live from OpenAlex

Coffeehouses have a long history as not only spaces of and for consumption but also as social settings that facilitate and encourage public sociality even in an epoch in which such spaces for sociability are alleged to be fading away. This paper comprises a study of coffeehouses with analytic perspectives and priorities that are very different from past research on this social form. The empirical focus here is on so-called “third wave” coffeehouses, which view coffee as an artisanal product and which deploy, among other resources, high-end equipment in their beverage creation. This equipment is itself an additional empirical focus, and the ways in which traditional face-to-face sociability and, in particular, interaction between customers and employees is facilitated by those machines is considered here. The theoretical perspective used here is ethnomethodological and as such a central concern with describing lived experience at these venues is accomplished by considering photographic evidence of machines and people in situ to see how machines, people, spaces and comestibles interact in these cafes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.174
GPT teacher head0.512
Teacher spread0.338 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations48
Published2014
Admission routes1
Has abstractyes

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