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Enregistrement W2768215055 · doi:10.13140/rg.2.2.29392.64001

Material deprivation in Canada

2017· preprint· en· W2768215055 sur OpenAlexaboutno aff
Geranda Notten, Julie Charest, Andrew Heisz

Notice bibliographique

RevueuO Research (University of Ottawa) · 2017
Typepreprint
Langueen
DomaineSocial Sciences
ThématiqueEnvironmental Justice and Health Disparities
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésIndex (typography)StatisticsRelative deprivationSocial deprivationEconometricsOfficial statisticsYield (engineering)PsychologyEconomicsDemographic economicsMathematicsComputer scienceSocial psychologyEconomic growth

Résumé

récupéré en direct d'OpenAlex

Material deprivation data are collected annually by the national statistics offices of many advanced economies and the resulting statistics are used by academics, policy makers and interest groups as a complement to low-income statistics. This paper presents the first nationally and provincially representative statistics on material deprivation in Canada. Using the one-time Canadian Survey of Economic Well-being (2013) we construct a material deprivation index, study the incidence and correlates of material deprivation across socio-demographic groups, and explore the overlap in incidence between material deprivation, low income and economic hardship.Our tests indicate that all available deprivation items meet the scientific criteria (suitability, validity, reliability and additivity) for inclusion in a material deprivation index. We further develop an empirical strategy that uses supplementary information in the CSEW to help set the material deprivation threshold: we assess whether a materially deprived person has a relatively high or low likelihood of being poor, thereafter analyzing how the composition of these groups changes as the threshold changes. The resulting material deprivation index includes 17 items and reflects the percentage of Canadians living in households that are deprived of two or more items. Setting the threshold is the most influential methodological decision: a threshold of two items yields a material deprivation rate of 18 percent, while thresholds of one item and three items yield rates of 29 and 13 percent respectively. We proceed the analysis with a threshold of two items. The appendix also offers all results for a threshold of three items. Other than finding a lower incidence of materialdeprivation, the general findings described below also hold for a threshold of three items.We find that the population identified as materially deprived only partially overlaps with the population identified as low-income using the Low-Income Measure (LIM). Because some Canadians are identified as having (only) a low income (8 percent), others as being (only) materially deprived (11 percent), and another group as both (8 percent), the total population that could be experiencing poverty level living conditions is considerably larger than what is measured by Canada’s low-income indicators (27 percent).Moreover, most socio-economic groups that have a high risk of low income also have a high risk of material deprivation. For these groups, the total population that could be experiencing poverty is substantively higher than for the general population. For instance, sixty percent of lone-parent households are either deemed poor by both indicators (33 percent), (only) materially deprived (17 percent) or (only) low-income (10 percent). However, some socio-demographic groups known to have a high risk of poverty according to one indicator do not also have a high risk according to the other indicator (or vice versa). For instance, persons aged 65 years and above have an above-average risk of having low income but an on average risk of being materially deprived. Families consisting of a couple with children have a below-average risk of having low income but an on average risk of being materially deprived.Finally, even though by far most materially deprived persons also report experiencing economic hardship (88 percent), there is also a significant population reporting economic hardship without being materially deprived. This suggests that economic hardship affects a broader population than that experiencing poverty. Economic hardship is defined as having, in the past year: experienced difficulty meeting necessary expenses; asked for help from friends or family, taken on debt, sold assets, or turned to a charity when short of money; and/or experienced financial difficulty due to a long-term disability or health problem.Concluding, these novel findings for Canada corroborate those of a large body of international research: identifying persons experiencing poverty level living conditions requires more than measuring low incomes alone; and, material deprivation indicators complement low-income indicators because they are better at screening the material well-being of persons with above (or below) ‘typical’ needs, costs of living, access to subsidized services, non-income financial resources and/or debt service.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,095
Score d'incertitude au seuil0,846

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,092
Tête enseignante GPT0,355
Écart entre enseignants0,264 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2017
Routes d'admission1
Résumé présentoui

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