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Record W4367155286 · doi:10.7202/1098783ar

Calories and Culture

2023· article· en· W4367155286 on OpenAlexvenueaboutno aff
Jake Breadman

Bibliographic record

VenueOntario History · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsFishingIndigenousConsumption (sociology)Food consumptionAgricultureCalorieGeographySociologyPolitical scienceSocial scienceEcologyAgricultural economicsLawEconomicsArchaeology

Abstract

fetched live from OpenAlex

This article analyzes what British soldiers in early-nineteenth century Upper Canada consumed in both peace and wartime, and how food and drink impacted human social relations between soldiers, officers, and Indigenous people. Consumption is about getting enough energy to survive, but it can also bind or break social relations. Here, both calories and culture, and the intrinsic connection between them, are analyzed. The first section looks at the calories which soldiers procured from food beyond their daily rations: fishing, agriculture and, sometimes, hunting and purchase. Out of these, fishing and hunting particularly divided enlisted men and officers. The availability of consumables, though, depended on class and environmental knowledge. Then the difficulties of hunting and fishing in wartime are outlined. Section two turns to culture: food and drink, and the rituals and settings surrounding consumption, positively and negatively impacted human social relations within the British army and with Indigenous people.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.213

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0090.015
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.019
GPT teacher head0.208
Teacher spread0.189 · 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
Published2023
Admission routes2
Has abstractyes

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