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Record W2808230326 · doi:10.4000/books.pum.8113

Les automobilistes du Québec en ont-ils pour leur argent ?

2014· book-chapter· fr· W2808230326 on OpenAlexaffabout
Dominique Nancy

Bibliographic record

VenuePresses de l’Université de Montréal eBooks · 2014
Typebook-chapter
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsCanadian Arthritis Patient Alliance
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Lourdement taxés, les automobilistes du Québec en ont-ils pour leur argent ? Non, répond Robert Gagné, directeur de la recherche et du transfert à HEC Montréal. « Le gouvernement fait de l’argent avec les automobilistes. Leurs contributions, incluant permis, immatriculation et taxes sur l’essence, ne sont pas réinvesties en totalité dans l’entretien et la réfection des routes. »Le gouvernement n’a aucune obligation à cet égard, précise le professeur. « Lorsque vous achetez une télévision, ri...

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: none
Teacher disagreement score0.061
Threshold uncertainty score0.440

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.003
Scholarly communication0.0050.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0160.001

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 head0.016
GPT teacher head0.209
Teacher spread0.193 · 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

Citations0
Published2014
Admission routes2
Has abstractyes

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