The balancing act: community agency leadership in multi-ethnic/multiracial communities
Notice bibliographique
Résumé
Toronto has become one of the most diverse cities in North America, and certainly the most diverse in Canada. In 2004 Toronto had the second-largest number of foreign-born residents of any major world city (UNDP, 2004). By 2011, nearly 50% of the total population were ethnic/visible minorities, with the top five visible minorities quickly becoming the ‘visible majority’; these included South Asians, making up 12.3% of the population; Chinese, 10.8%; Black, 8.5%; Filipino, 5.1%; and Arab/West Asian/Afghan (that is, Assyrian and Iranian), 3.1% (Statistics Canada, 2011). In such an ethnically diverse environment, challenges are inevitable. Since ethnicity is a contested term with varying ontological and epistemological challenges I will borrow Varshney's definition to nail down how I intend to relate to the term. By ethnicity I mean a ‘term which designates a sense of collective belonging, which could be based on common descent, language, history, culture, race, or religion (or combination of these)’ (Varshney, 2007, p 277). The communities on which this chapter focuses are nestled within two of the most diverse federal political boundaries in Canada – York West and York South Weston – in Northwest Toronto. In York West, over 72% of the population is non-white, while in York South Weston over 50% of the population is non-white. In York West, the top three ethnic groups proportionately are White (27.5%), Black (22.4%),and South Asian (16.0%). In York South Weston the top three groups are White (44.9%), Black (21.1%) and Latin American (9.0%) (City of Toronto, 2011). Within each of these political boundaries are three communities, whose real names have been altered, which we will call Days, Chalks and Falls. Days is ethnically dominated by South Asians; Falls comprises predominantly Somalis and Black/Afrodisaporic Caribbean peoples; and Chalks comprises predominantly Spanishspeaking peoples. This categorisation of course begs the question as to whether or not Somalis are Black and requires deeper analysis than I can provide here. This classification is based solely on self-segregation of peoples in the communities. Although the primary focus of the chapter will be on my work with these communities, I will draw on community work in other communities in Toronto, as I have similar experiences throughout. These communities are part of, or very close to, communities identified by the city of Toronto as Neighbourhood Improvement Areas (NIA), classified as such because of the lack of resources and levels of poverty.
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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 | 0,007 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,008 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,004 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».