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Record W1486083606

Imposing Discipline Upon Nature: Gardens, Agriculture and Animal Husbandry in Cape Breton, 1713-1758

2006· article· en· W1486083606 on OpenAlexaffabout
Kenneth Donovan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsParks Canada
Fundersnot available
KeywordsForestryGeographyHumanitiesArchaeologyArt
DOInot available

Abstract

fetched live from OpenAlex

This paper examines horticulture in Ile Royale (Cape Breton) and focuses on the French attempt to grow food through the introduction of gardens, animals and small mixed farms (menageries). Adapting to the colder climate and marginal soil of first, Newfoundland, and then Cape Breton, the French introduced innovative solutions to the difficulties of land infertility. The French had confidence—given enough manpower—that anything was possible. By building roads, bridges, filling marshes, removing rocks, transporting rich soil, making raised beds, creating ponds, wells, fountains, using glass bells, fertilizer, seaweed, lime and compost, they imposed a discipline upon nature and transformed the most barren ground into bountiful gardens. Résumé Cet article sur l’horticulture dans l’Île Royale (Cap-Breton) décrit les efforts des Français pour subvenir à leurs besoins alimentaires au moyen de potagers, de bétail et de petites fermes mixtes («ménageries»). Pour composer avec le climat plus froid et le sol mince de Terre-Neuve, puis du Cap-Breton, les Français ont appliqué diverses solutions novatrices au problème de la pauvreté des sols. Convaincus que rien n’était impossible s’ils y mettaient la main-d’œuvre suffisante, les Français ont construit des routes et des ponts, rempli des marécages, épierré les sols, importé du terreau fertile, aménagé des plates-bandes surélevées, créé des étangs, des puits et des fontaines, utilisé des cloches de verre, de l’engrais, des algues, du calcaire et du compost, bref, ils ont plié la nature à leurs besoins et transformé les terres les plus pauvres en généreux potagers.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.526

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.006
GPT teacher head0.192
Teacher spread0.186 · 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 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

Citations5
Published2006
Admission routes2
Has abstractyes

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