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Record W4226508299 · doi:10.1353/sec.2022.0008

Marvelous Maples: Visions of Maple Sugar in New France, 1691–1761

2022· article· en· W4226508299 on OpenAlexaboutno aff
Nathan Brown

Bibliographic record

VenueStudies in eighteenth century culture/Studies in eighteenth-century culture · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMapleIndigenousSugarVisionOrder (exchange)HistorySociologyBiologyBotanyEcologyEconomicsAnthropologyFood science

Abstract

fetched live from OpenAlex

Maple sugar was a multivalent product in the New France. Before the “discovery” of maples by early American boosters like Thomas Jefferson or Benjamin Rush, French settlers in Canada had already developed a deep connection to maple sap and its sugary products. Although it failed to enter the world market in the eighteenth century like its cane cousin, maple sugar held intriguing—but ultimately unrealized—possibilities for New France within a mercantilist framework. This natural sweetener also fueled a utopian vision of New France and troubled eighteenth-century French beliefs about their own mastery of knowledge, the environment, technology, and the Indigenous Peoples of North America. This article assesses descriptions of maple sugar in both French texts, such as those by Sieur de Dièreville, Baron de Lahontan, Joseph-François de Lafitau, and Pierre-Xavier de Charlevoix, as well as texts associated with several Indigenous nations of the Great Lakes in order to explore the history of sweetness beyond the sugar plantation.

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.752
Threshold uncertainty score0.492

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0080.007
Scholarly communication0.0040.003
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.039
GPT teacher head0.286
Teacher spread0.246 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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