Impact des coûts de transport sur la compétitivité des entreprises québécoises
Bibliographic record
Abstract
Le mandat de cette étude visait à creuser davantage la question des coûts et niveaux de service offerts en région en allant au-delà de l'étude de KPMG (2009) qui se limitait aux coûts reliés camionnage sur un territoire géographique relativement limité. La présente étude vise donc à dresser un portrait plus complet des coûts de transport et de la qualité des services de transport disponibles dans les régions du Québec et ce, pour l'ensemble des modes de transport utilisés, incluant le transport intermodal. Même si la taille de l'échantillon utilisé (20 entreprises) nous empêche de présenter des conclusions définitives sur la question, les résultats obtenus apportent toutefois un éclairage nouveau et pertinent sur les enjeux reliés aux coûts de transport en région au Québec.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".