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Ending Street Homelessness in Vanguard Cities Across the Globe: An International Comparative Study

2022· report· en· W6990848060 sur OpenAlexaboutno aff

Notice bibliographique

RevueIssue Lab (Candid) · 2022
Typereport
Langueen
Domaine
Thématique
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésVanguardGlobeOutreachInvestment (military)AttractivenessRedevelopmentPoverty
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Street homelessness is one of the most extreme, and visible, manifestations of profound injustice on the planet, but often struggles to achieve priority attention at international level. The Institute of Global Homelessness (IGH's) A Place to Call Home initiative, launched in 2017, represented a concerted effort to support cities across the globe to eradicate street homelessness. A first cohort of 13 'Vanguard Cities' committed to a specific target on ending or reducing street homelessness by December 2020. Our independent evaluation of this initiative found that:Two Vanguard Cities – Glasgow and Sydney – fully met their self-defined target reductions for end 2020. In addition, Greater Manchester, while it did not meet its exceptionally ambitious goal of 'ending all rough sleeping', recorded an impressive 52% reduction against baseline.Overall, there was evidence of reductions in targeted aspects of street homelessness in over half of the Vanguard Cities. In most of the remaining cities data limitations, sometimes as a result of COVID, meant that it was not possible to determine trends. In only one Vanguard City – Edmonton – was there an evidenced increase in street homelessness over baseline levels.Key enablers of progress in reducing street homelessness included the presence of a lead coordinating agency, and coordinated entry to homelessness services, alongside investment in specialized and evidence-based interventions, such as assertive street outreach services, individual case management and Housing First.Key barriers to progress included heavy reliance on undignified and sometimes unsafe communal shelters, a preoccupation with meeting immediate physiological needs, and sometimes perceived spiritual needs, rather than structural and system change, and a lack of emphasis on prevention. Aggressive enforcement interventions by police and city authorities, and documentary and identification barriers, were also counter-productive to attempts to reduce street homelessness.A key contextual variable between the Vanguard Cities was political will, with success in driving down street homelessness associated with high-level political commitments. An absolute lack of funds was a major challenge in all of the Global South cities, but also in resource-poor settings in the Global North. Almost all Vanguard Cities cited pressures on the affordable housing stock as a key barrier to progress, but local lettings and other policies could make a real difference.The impact of the COVID-19 crisis differed markedly across the Vanguard Cities, with people at risk of street homelessness most effectively protected in the UK and Australian cities. Responses were less inclusive and ambitious in the North American and Global South cities, with more continued use of 'shared air' shelters, albeit that in some of these contexts the pandemic prompted better coordination of local efforts to address street homelessness.IGH involvement was viewed as instrumental in enhancing the local profile, momentum and level of ambition attached to reducing street homelessness in the Vanguard Cities. IGH's added value to future cohorts of cities could be maximised via a focus on more tailored forms of support specific to the needs of each city, and also to different types of stakeholders, particularly frontline workers.

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)0,004
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,519
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0040,000
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0030,002
Intégrité de la recherche0,0000,002
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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 Opus0,077
Tête enseignante GPT0,412
Écart entre enseignants0,335 · 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.

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

Citations0
Publié2022
Routes d'admission1
Résumé présentoui

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