David A. Green and Jonathan R. Kesselman, Eds. Dimensions of Inequality in Canada
Notice bibliographique
Résumé
David A. Green and Jonathan R. Kesselman, eds. Dimensions of Inequality in Canada. Vancouver: UBC Press, 2007. 477 pp. Index. $29.95 sc. Dimensions of Inequality in one of three edited volumes that came about from Equality, Security, and Community project. The project was conducted over a six-year period with purpose of explaining and improving distribution of in Canada (ii). The book provides an overall assessment of in Canada. The most common income. A survey of income over 1990s using three data sources has come to different conclusions (due to difference in way income reported). Survey data stable levels of whereas more reliable tax and census data point to rapid increases in income during 1990s (15). Measurements of in terms of consumption have been similar to that of survey data. However, earnings mobility is dynamic complement of inequality (101). The probability of staying in same earnings category higher for women than for men. The probabilities of moving up distribution are generally higher for men, whereas probabilities of moving down one or more earnings categories are higher for women (108). Mobility also much greater toward bottom of earnings distribution than at top end where high-skill workers enjoy much more stable earnings patterns (123). Unfortunately, movements within earnings distribution follow a pattern in which rich tend to stay rich and tend to stay poor (14-15). Examining employment levels another method of measuring inequality. Disturbing trends are evident in differences in working time of adults. According to data from International Labour Organization, in twenty-year period between 1980 to 2000 average actual working time per adult (ages fifteen to sixty-four) rose in United States by 234 hours to 1,476 while falling in Germany by 170 hours to 973 (155). Moreover, relatively in United States work significantly harder and still end up with less income than their European counterparts (i.e., France, Germany, Sweden and United Kingdom). Leisure time (an indicator of economic well-being) has a direct impact on an individual's money income level. However, because of substantial variation in leisure time between countries, of level of money income likely understate degree of differences in of economic well-being (179). Compared to Europe, the distribution of economic among Canadians even more unequal then money income comparisons alone would indicate (179). Ethnic and visible minorities face prevalent economic and health inequalities. All groups of Aboriginals are disadvantaged not only in wages and salaries but also self-report highest cases of major chronic diseases. …
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».