Predicting who applies to Public Housing using Linked Administrative Data
Notice bibliographique
Résumé
ABSTRACT ObjectivePublic housing residents, who live in low income government rental housing, are often in poorer health than the rest of the population. However, few studies have been able to untangle the relationships between health and public housing residency, and to assess whether health contributes to the decision to apply. We used linked population-based administrative data from one Canadian province to compare the health and health service use of people who applied to public housing to that of people who did not apply. ApproachAdministrative data housed in the Manitoba Centre for Health Policy’s Population Health Research Data Repository were used to identify a cohort of individuals who applied to public housing in 2005 and 2006. They were matched one-to-one to a cohort from the general population using socio-demographic variables. A population registry provided demographic and geographic characteristics. Economic measures included receipt of income assistance and an area-level measure from the Statistics Canada Census. Measures of health and health service use were derived from hospital, physician, emergency department, and prescription drug databases. Conditional logistic regression was used to test the association between a public housing application and health status and health service use, after controlling for income. ResultsThere were 10,324 individuals in each of the public housing applicant and matched cohorts; the majority were female (72.4%), young (62% less than 40 years), urban residents (61.2%), and received income assistance (52.8%). A higher percent of the public housing applicant cohort had physician-diagnosed physical and mental health conditions and used more health services compared to the matched cohort. Having a physician-diagnosed respiratory illness (odds ratio [OR] = 1.14, 95% confidence interval [CI] 1.05,1.25), diabetes (OR = 1.24, 95% CI 1.09,1.40), schizophrenia (OR = 1.58, 95% CI 1.30,1.92), affective disorders (OR = 1.37, 95% CI 1.27,1.48), and substance abuse disorders (OR = 1.46, 95% CI 1.25,1.71) were associated with an increased likelihood of applying for public housing, while being diagnosed with cancer (OR = 0.76, 95% CI 0.61,0.96) was associated with a decreased likelihood of applying, after controlling for income differences. High health service users were also more likely to apply for public housing, after controlling for income differences. ConclusionIndividuals who move into public housing are in poor health before they apply. Health and social service supports that are co-located with public housing facilities may help to ensure that residents have successful tenancies.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».