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Record W4405107811 · doi:10.3366/irss.2024.0037

‘Hunger Added the Best of Sauce’: The Foodways of Women Innkeepers in the Highlands and Islands of Scotland, <i>c</i>. 1770–1840

2024· article· en· W4405107811 on OpenAlexvenueno aff
Theresa Mackay

Bibliographic record

VenueInternational Review of Scottish Studies · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFoodwaysHistoryGeographyAnthropologySociology

Abstract

fetched live from OpenAlex

In the eighteenth and nineteenth centuries, English and Scottish gentry-class travellers took journeys into the Highlands and Islands of Scotland and wrote about their experiences. They made observations about foods, especially meals cooked and served by women innkeepers, at accommodations along the way. By analyzing written travellers’ accounts, this study uncovers foodways and the daily lives of women who were working—and cooking—as innkeepers in the Highlands and Islands, circa 1770 to 1840. It establishes that, with some noted exceptions, foods that women innkeepers offered at inns were repetitive for reasons of choice, economy, familiarity with practices, and labour efficiencies. Habitus, including preferences for certain foods and forms of service, greatly influenced guests’ reviews, reinforcing class and cultural differences between travellers and innkeepers. This article argues, however, that despite these differences, guests acknowledged and appreciated how innkeepers made concerted efforts to appease their tastes and abate hunger, reinforcing the idea that women innkeepers had power and agency as they leveraged their kitchen meshwork. Finally, despite a common narrative of the ‘bad Highland inn,’ the evidence discussed suggests that guests felt women innkeepers excelled at some meals, saying the food was at times unexpectedly plentiful and delicious.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.727
Threshold uncertainty score0.240

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.037
GPT teacher head0.281
Teacher spread0.243 · 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.

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