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Record W4415899477 · doi:10.5539/ijel.v15n7p43

Health and Food Discourses in The Englishwoman’s Domestic Magazine (1852–60)

2025· article· W4415899477 on OpenAlexvenueno aff
Martina Guzzetti

Bibliographic record

VenueInternational Journal of English Linguistics · 2025
Typearticle
Language
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsnot available
FundersEuropean Commission
KeywordsOrder (exchange)Health promotionKey (lock)Focus (optics)Promotion (chess)Target audience

Abstract

fetched live from OpenAlex

Samuel and Isabella Beeton’s Englishwoman’s Domestic Magazine (1852–79), a key periodical for middle-class women in Victorian England, is best remembered for features like culinary recipes, fashion plates and embroidery patterns. However, it also contained regular columns about the treatment of illnesses and the promotion of health and wellbeing. This contribution considers a corpus of 140 articles taken from the column “The sick room and nursery” and from classified ads published regularly in the magazine between 1852 and 1860 in order to focus on the topic of health and nourishment. Specific corpus queries demonstrate the pervasiveness of discourses related to food, diet, and nutrition both as promoters of health and as key factors in recovering from diseases. Moreover, the attention on previously generally neglected sections of the magazine aims to shed more light on the importance of food discourses that went beyond the simple recipes, while at the same time contributing to the dissemination of medical knowledge to lay readers (mainly, but not exclusively, middle-class women in this case). By tracing these discourses, the article reveals how the periodical functioned not only as a guide for domestic management, but also as a tool for socialising women into specific health practices.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.994
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0060.007
Scholarly communication0.0050.004
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.016
GPT teacher head0.294
Teacher spread0.278 · 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.

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
Published2025
Admission routes1
Has abstractyes

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Same venueInternational Journal of English LinguisticsSame topicCulinary Culture and TourismFrench-language works237,207