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Record W6964101932 · doi:10.25318/1110002601-fra

La durée de faible revenu des déclarants au Canada

2019· dataset· fr· W6964101932 on OpenAlexaboutno aff

Bibliographic record

VenueStatistics Canada Dissemination · 2019
Typedataset
Languagefr
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsIle de franceCote d ivoireLimiting

Abstract

fetched live from OpenAlex

Ce tableau contient les statistiques qui décrivent la durée des périodes de faible revenu vécues par les déclarants canadiens au cours d’une période de huit ans. Une période de faible revenu désigne une période au cours de laquelle une personne reste dans une situation de faible revenu. Elle peut durer un an ou plusieurs années consécutives. La longueur de la période fait référence à sa durée et est exprimée en années. La mesure de faible revenu (MFR) est utilisée pour déterminer les déclarants à faible revenu. Le seuil de la MFR correspond à 50 % de la médiane du revenu familial ajusté après impôt de tous les déclarants et des membres de leur famille. Le tableau utilise deux types de MFR : la MFR variable est fondée sur le revenu total médian recalculé chaque année, alors que la MFR fixe est fondée sur le revenu total médian de 2002 ajusté annuellement par l’Indice des prix à la consommation pour l’ensemble des produits et services.

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)0.006
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 score0.016
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.014
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.003

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 head0.010
GPT teacher head0.274
Teacher spread0.263 · 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
Published2019
Admission routes1
Has abstractyes

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Same venueStatistics Canada DisseminationFrench-language works237,207