How Many Housed People in Calgary are at Risk of Homelessness?
Notice bibliographique
Résumé
Significant numbers of people and families in Calgary face financial challenges that put them at risk of homelessness. The authors first define different levels of risk, in order to focus on people at high risk of slipping into homelessness. The authors assume, based on the findings of previous studies, that people faced with financial hardship make all possible budgetary changes to lower their cost of living and thereby retain housing. These changes include using food banks, relying on charities, eating less nutritious diets, living in more crowded conditions, moving to housing with lower rent and giving up any hope of maintaining what the designers of Canada’s poverty line define as a “modest and basic standard of living.” The highest risk category comprises those who have exhausted nearly all efforts to maintain their housing and are extremely vulnerable to even minor shocks to income or living costs. Estimating the number of people and households in Calgary at high risk of homelessnessrelies on key assumptions about housing costs, family structure, food budget, and expenditure reduction. The authors show how their estimates of the number of housed people at high riskof homelessness varies by these assumptions. These calculations provide insight into the effects of rent increases and food inflation on the ability of people with very low income to maintain housing. In doing so, they also provide evidence of how relatively small adjustments to income, rent, and food prices can pull people from the brink of homelessness. The estimates indicate that between 102,635 and 124,375 people in Calgary, including both adults and children, were at high risk of homelessness in 2016. The authors indicate they feel comfortable in supporting a number near the midpoint of this range, approximately 115,000 people, as the number of people at high risk of homelessness in Calgary in 2016. This at-risk population lived in approximately 40,000 households. An estimate for 2023 would need to account for higher rents and food prices but also higher incomes relative to what were observed in 2016. While the authors suggests that the at-risk population is likely higher now than it was in 2016, they note that even were this not true, the 2016 estimate of approximately 115,000 people living in 40,000 households ought to be more than enough to spur policymakers into acting. The encouragement to be found in these calculations is that relatively modest policy interventions have large impacts on the size of the population at risk of homelessness. Consistent with research elsewhere, extreme policy interventions are not required to pull large numbers of people from the brink of homelessness. The most important characteristic of these policy interventions is not their size, but simply the fact they are acted upon.
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 | 0,000 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 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 ».