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Enregistrement W4388490988 · doi:10.59490/abe.2017.12.3615

Introduction

2018· article· en· W4388490988 sur OpenAlex
Donya Ahmadi

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Notice bibliographique

RevueArchitecture and the Built Environment · 2018
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueCrime Patterns and Interventions
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésComputer science

Résumé

récupéré en direct d'OpenAlex

On May 23, 2007, 15 year old Jordan Manners was shot and killed in a hallway inside the C. W. Jeffreys high school in the Jane‑Finch neighbourhood of Toronto. Four days later, two 17-year-old male suspects, who lived in the same neighbourhood, were arrested and charged with first-degree murder. In the aftermath of this shooting, Jane‑Finch appeared in virtually every Canadian news outlet. Despite a lack of insight into the motives of the accused males whose identities were protected due to the Youth Criminal Justice Act, the media heavily framed the shooting as having roots in the very nature of Toronto’s racialized poor inner-suburbs (O’Grady, Parnaby, and Schikschneit, 2010). The neighbourhood of Jane‑Finch in north-west Toronto has since gained considerable publicity for its high crime rate and concentrated poverty. Today Jane‑Finch is considered one of the most stigmatised neighbourhoods in Canada, heavily associated with guns, gangs and racial divide (Richardson, 2008). A post-war modernist estate accommodating a predominantly poor racialized population, Jane‑Finch is by no means the first of its kind to receive such negative and mixed coverage by the media. A 2010 study of deprived communities in Glasgow documented a high recognition of the existence of negative external reputations among residents in peripheral housing estates (GoWell, 2010). In 1999, a study of 500 Danish estates, contended that the concentration of ethnic minorities in an area was among the most important factors in explaining poor external reputation (Skifter-Andersen, 1999). Similarly, in a study focusing on housing estates in Utrecht, Permentier et al. (2011) found that ethnic composition and average income strongly influenced the perceived neighbourhood reputation. The same study concluded that distance to the city centre was negatively associated with neighbouthood reputation, i.e. the farther the neighbourhood from the centre, the worse its external ‘image’. The framing of Jordan Manners’ death by the media is llustrative of essentialised and stereotypical representations of poor, ethnic-minority communities. As stressed by O’Grady et al. (2010) “the ‘cause’ of the shooting was framed in a fashion that was suggestive of social and/or cultural inferiority (single-parent families, unwed mothers, welfare dependency, a high concentration of subsidized housing, etc.) […] A dysfunctional local community was seen as ostensibly the root cause of Jordan Manners’ death”. The negative reputation of Jane‑Finch is established and sustained along not only the axis of race and class, but also gender, since single mothers are the ones commonly blamed for the stigmatisation and criminalisation of the area since they are seen as “the producers of unruly youth.” (Narain, 2012: 80). Narain (2012) underscores that Toronto’s lower-income neighbourhoods are often ‘racialized’, a categorization which is attributed not just to the concentration of visible minority households, but also the lack of social, economic and political resources in these areas (Teelucksingh, 2007). However, while Toronto’s racialised poor communities have become social locations of fear and othering (Narain, 2012), celebration of diversity has become a popular theme in Toronto’s policy and image making, such that many policy documents have proclaimed diversity as the city’s biggest strength. But why is it that some communities are celebrated for their diversity, while others are criminalised and stigmatised? Like many other countries across Western Europe and North America, Canada has experienced considerable economic restructuring in the past decades, which has rendered the market a more prominent actor in social regulation of Canadian cities. Various studies over the years have shown that economic restructuring has intensified the processes of racialization and feminization in the labour market, leading to increased economic, social and political inequality. Racialized groups, immigrants, refugees and women have particularly suffered the consequences of restructuring. As well, many Canadian urban centres have experienced considerable polarisation along the lines of income and race (Galabuzi, 2005; Galabuzi, 2001; Jackson, 2001; Yalnyzian, 1998). Ethnic minority residents and aboriginal peoples are, as stressed by Galabuzi (2005), “twice as likely to be poor as other Canadians because of the intensified economic and social and economic exploitation of these communities whose members have to endure historical racial and gender inequalities accentuated by the restructuring of the Canadian economy and more recently racial profiling. (17)” Galabuzi (2005) has used the term ‘racialisation of poverty’ to refer to the process by which poverty has become more concentrated and reproduced inter-generationally among racialized group members in cities such as Toronto. This process is manifest through “a double digit racialized income gap, higher than average unemployment, differential labour market participation, deepening and disproportionate exposure to low income, differential access to housing leading to racial segregation, disproportionate contact with the criminal Justice system, particularly for racialized youth leading to the criminalization of youth and higher health risks. (38)” The racialisation of poverty in Canadian cities further seems to follow a specific geographic pattern since increasingly, racialized people are settling in peripheral areas which are characterized by high poverty and unemployment rates, welfare dependency, and high school dropout rates, all of which are condition that reproduce poverty. Often they find themselves surrounded by others in similar circumstances in neighbourhoods that are heavily populated and segregated from the rest of society (Ibid). Racialised groups living in these geographical areas further deal with social deficits such as inadequate access to counselling services, life skills training, child care, recreation, and health care (Galabuzi, 2005; Kazemipur and Halli 2000). The racialization of poverty has further had a major impact on neighbourhood selection and access to adequate housing for new immigrants in Toronto who are much more likely than nonimmigrants to live in racially segregated neighbourhoods with high rates of poverty (Ibid). Hulchanski (2010) similarly argues that the city is falling apart into ‘three cities’, i.e. three areas with distinct income and racial characteristics, underscoring that the low-income (mainly newcomer or ethnic) neighbourhoods, located in the inner-suburbs of the city, have been consistently facing decreasing income levels since the 1980s. Despite evidence for segregation and stigmatization of racialized neighbourhoods in Toronto, diversity remains a popular catchphrase with an appealing ring both to policy makers and mainstream society. In fact, Toronto’s long-standing immigration history coupled by the introduction of the Canadian Multiculturalism policy in the 1970s have rendered diversity a prominent value for Torontonians (Ahmadi and Tasan-Kok, 2014). Diversity is largely framed as a ‘marketable asset’ in Toronto’s policy context (Boudreau et al., 2009). Kipfer and Keil (2002) underscore that diversity functions as the primary aesthetic backdrop to the city’s beautification and development plans. They further argue that the promotion of Toronto as a diverse global city is connected to the social cleansing of inner city Toronto, through racialised segregation, racial profiling and repressive policing. Diversity management in Toronto, thus, may be more preoccupied with promoting a more competitive city image than tending to the realities of racialised poverty and segregation in the city. It thus appears that while the celebration of diversity has attracted funds and services to inner city areas, stereotyping based on different categories of diversity (especially ethnicity and class) has resulted in the stigmatization and criminalization of poor peripheral neighbourhoods. Herein lies an important question: why is diversity sometimes regarded as an asset and sometimes a deficit? And is it possible to move beyond such dichotomous understanding of the notion? Answering these questions firstly requires understanding what the concept of diversity means and how it has come to be defined in theoretical and policy debates. What is diversity? Diversity in urban areas may derive from multiple factors such as behaviour, lifestyles, activities, ethnicity, age, gender and sexuality profiles, entitlements and restrictions of rights, labour market experiences, and patterns of spatial distribution. Traditionally, diversity has been defined adopting different unidimensional approaches which consider diversity across a single dimension at a time (e.g. ethnicity) (Gopalda and DeRoy, 2015). A common critique of these approaches is that they fail to take account of the complexity of diversity, and the multiple and dynamic affiliations of an individual. Furthermore, unidimensional definitions of diversity may result in generalisations and stereotyping on the basis of categories such as ethnicity, gender, and socioeconomic class. By contrast, there have been a number of recent theoretical efforts to capture the complexity of diversity, perhaps the most notable of which is the notion of Super-diversity developed by Steven Vertovec in 2007. Grounded in the critique of the ‘ethnic lens’ in diversity and migration studies, super-diversity is a multidimensional perspective on diversity which goes beyond the ethnic group as the only object of study and acknowledges the interplay of multiple factors that impact people’s living conditions (Vertovec. 2007). Despite its contribution to capturing the complexity of urban diversity, super-diversity has received criticism for matters ranging from its epistemological shortcomings (difficulties in operationalization and research conduction) to its potential f

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.

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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,899
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

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

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 Opus0,012
Tête enseignante GPT0,272
Écart entre enseignants0,260 · 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