Relation entre les inégalités de revenu, la redistribution et la croissance économique dans quatre provinces canadiennes (Québec, Ontario, Alberta, Colombie-Britannique)
Bibliographic record
Abstract
Cette etude porte sur la relation entre les inegalites de revenu, la redistribution et la croissance economique dans les provinces d’Ontario, du Quebec, d’Alberta et de la Colombie-Britannique. A travers les recents travaux de Berg & al. (2018), nous avons analyse cette relation avec la nouvelle definition utilisee pour determiner la redistribution. Apres avoir examine la litterature, nous sommes parvenus a la conclusion qu’il existe deux courants d’analyse sur la relation entre les inegalites de revenu et la croissance economique. Ceux qui montrent que les inegalites ont un impact negatif sur la croissance et ceux qui pensent que les inegalites incitent a une augmentation de la croissance economique. Notre analyse montre que les inegalites restent prejudiciables a la croissance economique. Quant a la relation entre redistribution et croissance economique, nos resultats d’analyse revelent que la redistribution est egalement nuisible a la croissance economique.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".