Bibliographic record
Abstract
Les ménages obtiennent les biens et services nécessaires au bien-être de leurs membres en bonne partie dans la sphère marchande. La marchandisation des biens et des services est désormais largement étendue, bien que le bien-être ne se réduise pas à la consommation marchande. Depuis 1969, les enquêtes budgétaires canadiennes permettent d’évaluer les comportements de consommation ainsi que la structure des besoins des ménages (régression du poids de l’alimentation et hausse du poids des postes transports, logement, loisirs et culture, protection et dépenses diverses). L’analyse de la différenciation transversale et temporelle des comportements de consommation entre classes socioéconomiques révèle que les ménages aisés accroissent leurs efforts budgétaires plus rapidement que les ménages pauvres et de classes moyennes inférieures pour les dépenses discrétionnaires et afin de satisfaire de nouveaux besoins. Quand un poste de consommation augmente rapidement lorsque le revenu des ménages s’accroît sur une longue période, il est plus différencié socialement, tel qu’illustré par l’évolution des dépenses pour le logement ou les transports.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 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".