MétaCan
Menu
Back to cohort
Record W6912993374 · doi:10.5683/sp3/8ygecs

Recensements du Canada 1665-1871, Bas Canada (Québec)

2023· dataset· fr· W6912993374 on OpenAlexaboutno aff

Bibliographic record

VenueBorealis · 2023
Typedataset
Languagefr
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsResearch methodologyOrder (exchange)

Abstract

fetched live from OpenAlex

Les tableaux de données portent sur les conditions sociales et économiques du Canada pré-confédération, du premier recensement en 1665 à la Confédération en 1867. Les tableaux ont été transcrits du quatrième volume du Recensement du Canada de 1871 : Réimpression des recensements du Canada, 1665-1871, disponible en ligne auprès de Statistique Canada, Canadiana, Publications du gouvernement du Canada et Internet Archive. Cet ensemble de données fait partie des trois ensembles qui couvrent l'histoire des recensements au Québec. Ces tableaux portent sur Bas-Canada pour les années 1825-1861. Pour les données des recensements des années 1765-1790, veuillez consulter l'ensemble de données de la province de Québec ; pour les données des recensements des années 1676-1754, veuillez consulter l'ensemble de données de la Nouvelle-France. Note concernant la terminologie : En raison de la nature de certaines sources de données, la terminologie peut inclure des termes problématiques et/ou offensants pour les chercheurs. Certains termes utilisés pour désigner des groupes ethniques, religieux et culturels sont propres à la période de collecte des données. Lorsque vous explorez ou utilisez ces données, faites-le dans le cadre des concepts de la pensée historique, en analysant non seulement le contenu, mais en posant des questions sur qui a façonné le contenu et pourquoi.

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)0.004
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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.056
Threshold uncertainty score0.406

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.024
Science and technology studies0.0040.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0380.005

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 head0.014
GPT teacher head0.223
Teacher spread0.209 · 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
GenreDataset

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

Explore more

Same venueBorealisFrench-language works237,207