Standardized observation of neighbourhood disorder: does it work in Canada?
Notice bibliographique
Résumé
BACKGROUND: There is a growing body of evidence that where you live is important to your health. Despite numerous previous studies investigating the relationship between neighbourhood deprivation (and structure) and residents' health, the precise nature of this relationship remains unclear. Relatively few investigations have relied on direct observation of neighbourhoods, while those that have were developed primarily in US settings. Evaluation of the transferability of such tools to other contexts is an important first step before applying such instruments to the investigation of health and well-being. This study evaluated the performance of a systematic social observational (SSO) tool (adapted from previous studies of American and British neighbourhoods) in a Canadian urban context. METHODS: This was a mixed-methods study. Quantitative SSO ratings and qualitative descriptions of 176 block faces were obtained in six Toronto neighbourhoods (4 low-income, and 2 middle/high-income) by trained raters. Exploratory factor analysis was conducted with the quantitative SSO ratings. Content analysis consisted of independent coding of qualitative data by three members of the research team to yield common themes and categories. RESULTS: Factor analysis identified three factors (physical decay/disorder, social accessibility, recreational opportunities), but only 'physical decay/disorder' reflected previous findings in the literature. Qualitative results (based on raters' fieldwork experiences) revealed the tool's shortcomings in capturing important features of the neighbourhoods under study, and informed interpretation of the quantitative findings. CONCLUSIONS: This study tested the performance of an SSO tool in a Canadian context, which is an important initial step before applying it to the study of health and disease. The tool demonstrated important shortcomings when applied to six diverse Toronto neighbourhoods. The study's analyses challenge previously held assumptions (e.g. social 'disorder') regarding neighbourhood social and built environments. For example, neighbourhood 'order' has traditionally been assumed to be synonymous with a certain degree of homogeneity, however the neighbourhoods under study were characterized by high degrees of heterogeneity and low levels of disorder. Heterogeneity was seen as an appealing feature of a block face. Employing qualitative techniques with SSO represents a unique contribution, enhancing both our understanding of the quantitative ratings obtained and of neighbourhood characteristics that are not currently captured by such instruments.
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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 | 0,011 | 0,032 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,005 | 0,003 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,003 |
| 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 ».