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Record W7001709184

Le jardin des Canadas : étude des cartes de Joseph Bouchette (1774-1841)

2023· other· fr· W7001709184 on OpenAlexaboutno aff

Bibliographic record

VenueArchipelago (Université du Québec à Montréal) · 2023
Typeother
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsColonial periodEthnographyNational identityHistorical heritage
DOInot available

Abstract

fetched live from OpenAlex

Au cours de leur histoire, les cartes coloniales ont été des lieux d’expérimentation, de nouvelles pratiques et de gestion d’aménagement de l’espace. Depuis la traite de fourrures, elles ont contribué à des transformations majeures sur le territoire, notamment avec la création des frontières, de réserves et l’exploitation des ressources forestières, et au 20e siècle, avec l’exploitation des ressources minières et hydroélectriques. Ce mémoire porte sur les cartes du Bas-Canada et du Canada de Joseph Bouchette (1774-1841) reconnues comme les premières cartes précises du Québec. À travers une étude intermédiale de la production matérielle de cet arpenteur – entre cartographie, paysage, littérature et architecture – ce mémoire se concentre sur la part des savoirs vernaculaires et des théories esthétiques britanniques dans la construction du territoire national – celles de la culture classique, du jardin anglais et du wilderness américain – tout en portant un regard sur la nature genrée de la production des savoirs géographiques en contexte colonial. L’objectif est également de démontrer la façon dont ces cartes témoignent d’une tension entre nomadisme des Premiers Peuples et la création de la sédentarité par la carte. _____________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : cartographie coloniale, paysage, littérature, architecture, savoirs autochtones, art du jardin, wilderness, esthétique, Québec, Canada

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.052
Threshold uncertainty score0.375

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0120.004
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.007
GPT teacher head0.168
Teacher spread0.161 · 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
GenreOther

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 routes1
Has abstractyes

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