Migrant women’s health and housing insecurity: an intersectional analysis
Notice bibliographique
Résumé
Purpose This paper presents an analysis of how health intersects with the experience of housing insecurity and homelessness, specifically for migrant women. The authors argue that it is important to understand the specificities of the interplay of these different factors to continue the advancement of our understanding and practice as advocates for health and housing security. Design/methodology/approach An exploratory, qualitative, methodological approach was adopted, using a broad definition of housing insecurity: from absolute homelessness (e.g. residing rough) to invisible homelessness (e.g. couch surfing) to those at risk of homelessness. In total, 26 newcomer (foreign-born women who came to live in Canada during the previous ten years, regardless of their immigration status) women were recruited in Montreal, Canada. Participants were recruited directly through advertisements in public places and in collaboration with community organizations (women’s centers, homeless shelters, crisis centers, domestic violence shelters, immigrant settlement agencies and ethnic associations) and they self-identified as having experienced housing insecurity. Efforts were made to include a diversity of immigrant statuses as well as diversity in ethnicity, race, country of origin, family composition, sexual orientation, age and range of physical and mental ability. Women were engaged in semi-structured, open-ended interviews lasting approximately 1 h. Interviews were conducted in English or French in a location and time of participants’ choosing. Findings The findings are presented around three themes: how health problems instigate and maintain migrant women’s housing insecurity and homelessness; ways in which women’s immigration trajectories and legal status may influence their health experiences; and particular coping strategies that migrant women employ in efforts to maintain or manage their health. The authors conclude with implications of these findings for both policy and practice in relation to migrant women who experience or are at risk of housing insecurity and homelessness. Originality/value Intersections of women experiencing migration and housing insecurity in Canadian contexts have rarely been examined. This paper addresses a gap in the literature in terms of topic and context, but also in terms of sharing the voices of migrant women with direct experience with housing insecurity.
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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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 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 ».