Homeless “Squeegee Kids”: Food Insecurity and Daily Survival. A study of food habits among homeless youth in Toronto
Notice bibliographique
Résumé
Food insecurity and homelessnessFood insecurity has been defined as the "limited or uncertain availability of nutritionally adequate and safe foods or limited or uncertain ability to acquire acceptable food in socially acceptable ways" (Anderson, 1990).In the 1990s, food insecurity among low-income households in affluent Western countries became an increasing concern, and considerable research was conducted on the causes and effects of food insecurity among low-income households and families.Little research has been done, however, on the relationship between homelessness and food insecurity.In an attempt to fill this gap, the authors undertook a study of homeless youth who frequented a downtown Toronto drop-in.What does food mean to teenagers and young adults in the chaotic world of life on the street?Where, how and what do they eat?How does their precarious access to food affect their health?The answers to these questions have implications for agencies and organizations that work with street youth. The study approachResearch was conducted at a downtown Toronto drop-in centre that is open on weekday afternoons, and is visited by 80 to 100 people a day.Although the dropin was used mostly by adults, at any time there were usually 5 to 15 youth present, clustered around one or two tables.The drop-in provided cooking facilities, but no food, although coffee and tea were available.Over the course of six months in 1998, Naomi Dachner regularly visited the drop-in centre for periods of three or four hours, with the permission of the coordinator.She would sit at the tables with the young people, chatting with them informally, asking questions, and recording their comments about food and meals.She also conducted six in-depth confidential interviews, each lasting up to two hours, in which the young people were encouraged to provide more details about their eating habits, living situation, educational background, length of time on the street, and coping strategies.The youth she interviewed were all over the age of 16 and none of them lived in hostels or shelters that provided regular meals.
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 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».