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Record W2945700895 · doi:10.29173/cons29365

The Thirst for Tea

2019· article· en· W2945700895 on OpenAlexaffvenue
Katlyn Kichko

Bibliographic record

VenueConstellations · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMateriality (auditing)NarrativeOrder (exchange)Tea partyGovernment (linguistics)AestheticsPolitical scienceSociologyHistoryLawBusinessArtPoliticsLiteraturePhilosophy

Abstract

fetched live from OpenAlex

This paper seeks to examine the smuggling of tea during the long eighteenth century through several facets. In order to understand why smuggling occurred throughout the eighteenth century, one must take into consideration the laws which necessitated the need for smuggling, as well as the economic environment of Britain throughout the century. In addressing the widescale phenomena of ritualized tea drinking, one can comprehend why tea, specifically, was selected to be smuggled, admittedly among a myriad of other valuable commodities. It is also critical to explore the materiality of tea ritual, as well as the smuggling process, as objects are a crucial element to the narrative and development of tea and its associated illicit activities. Bringing these components of examination together, one may begin to understand why tea was smuggled during the eighteenth century, and how the British government consequently worked to end smuggling altogether.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.023
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.005
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.002

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 head0.035
GPT teacher head0.214
Teacher spread0.179 · 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

Citations2
Published2019
Admission routes2
Has abstractyes

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