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Record W1992903025 · doi:10.7202/304442ar

La colonisation de la seigneurie de Batiscan aux 17e et 18e siècles : l’espace et les hommes

2008· article· fr· W1992903025 on OpenAlexvenueaboutno aff
Philippe Jarnoux

Bibliographic record

VenueRevue d histoire de l Amérique française · 2008
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPolitical science

Abstract

fetched live from OpenAlex

Cet article examine l'occupation du sol et le peuplement de la seigneurie de Batiscan, le plus important fief du gouvernment de Trois-Rivières, pendant le Régime français. L'analyse du milieu naturel, du mouvement et de la forme des concessions amène la constatation que les Jésuites, seigneurs depuis 1639, ont exercé une influence profonde pour structurer l'occupation du sol en délimitant les aires successifs d'expansion et en récompensant leurs serviteurs et les plus importantes familles afin d'encourager le développement de leur seigneurie. Suit une analyse de l'évolution démographique qui tient compte des migrations internes et externes et des relations humaines qui se tissent entre les habitants. Le développement précoce et intensif de la seigneurie en fait la plus populeuse de la région de Trois-Rivières dès la fin du 17 e siècle lorsque les rives du Saint-Laurent sont occupées et que la colonisation progresse en amont de la Batiscan. L'accroissement de la population au 18 e siècle est surtout canalisé vers de nouvelles zones pionnières à l'arrière du fief dans la paroisse de Sainte-Geneviève qui ouvre ses registres en 1727. En identifiant les divers facteurs qui ont influencé le développement de la société rurale cet article constitue une contribution originale à l'histoire de la colonisation de la Nouvelle-France.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.318

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)0.0050.000

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 head0.015
GPT teacher head0.245
Teacher spread0.230 · 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 designObservational
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

Citations4
Published2008
Admission routes2
Has abstractyes

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