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Record W4405098806 · doi:10.22215/etd/2024-16329

Brewster and Alewife: Perceptions of Female Brewers and Publicans in Early Modern England

2024· dissertation· en· W4405098806 on OpenAlexaff
Emilia Christina Dashko

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicWine Industry and Tourism
Canadian institutionsCarleton University
FundersStrong
KeywordsModernization theoryBrewsterBrewingBalladIndustrialisationPosition (finance)Political scienceEconomic historyArtHistoryBusinessLawLiterature

Abstract

fetched live from OpenAlex

The early modern period in England saw a lot of major changes in the brewing and victualling trades.Previously, beer had been a woman's domestic chore or a by-industry with which to earn a little extra income for the family.However, as brewing and victualling became more standardized and formalized starting with the introduction of hops in the 1400s, women soon found themselves being pushed out of the industry.This paper examines the portrayal of the brewsters and alewives who remained in the industries long after most women had left.It considers the consequences of modernization and industrialization of the beer industry in the sixteenth and seventeenth centuries.It shows how the women who remained in the industries after the fact navigated these changes, and how their position as relatively independent people was both feared and respected by their communities.By analyzing the popular media of the time, particularly broadside ballads, plays, paintings, and woodcuts, this paper explores the various way alewives and brewsters were represented and perceived by their customers, families, and neighbours.listened to on repeat because it always got me writing.To my two local watering holes, The Glebe Central Pub and The Aulde Dubliner, where I spent hours writing in the middle of a crowd with my headphones in and a beer at my side.To Camille, who knows half of my beer spiel off by heart because of how often you've heard me talk about my research.And to my partner, PJ, whose love and encouragement made sure I finished writing.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.271

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0060.004
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.013
GPT teacher head0.236
Teacher spread0.222 · 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 designQualitative
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

Citations0
Published2024
Admission routes1
Has abstractyes

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