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Enregistrement W2752767501

Fringe Banking in Canada: A Study of Rotating Savings and Credit Associations (ROSCAs) in Toronto’s Inner Suburbs

2017· article· en· W2752767501 sur OpenAlexvenueaboutno aff
Caroline Shenaz Hossein

Notice bibliographique

RevueCanadian journal of nonprofit and social economy research · 2017
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueMicrofinance and Financial Inclusion
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésChequeMicrofinanceFinancial servicesFinancial inclusionUnbankedFinanceCredit cardBusinessCashEconomicsSociologyPaymentEconomic growth
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

INTRODUCTIONIn December of 2014, Haitian-born Canadian Frantz St. Fleur was wrongfully arrested for allegedly depositing a fraudulent cheque of $9,000CND in his account at a Toronto Scotia Bank location where he had been a customer for ten years (Alamenciak, 2014). It turns out that his realtor legitimately issued the cheque after the sale of St. Fleur's property. Scotia Bank profusely apologized for this humiliating experience (Alamenciak, 2014). Such a confrontation with commercial bankers is an experience that many racialized Canadians encounter when they carry out banking (Hossein, 2015) This case of bias in the bank is one example of the many forms of economic discrimination faced by racialized Canadians (Das Gupta, 2007; Galabuzi, 2006; Gilmore, 2015). It may explain partially why people organize rotating savings and credit associations (ROSCAs). The attitude of commercial bankers toward racialized and low-income people makes it understandable why some Canadians do not trust bankers and will make sure they have a variety of financial devices, including informal ones.In the book Fringe Banking, Jerry Buckland (2012) examines the financial exclusion of Canadians in major cities, and how they turn to alternative financial service providers to meet their business and livelihood needs. Private cash-money places such as Money Mart dominate the news on what alternative financial providers are. Citizens and community organizations such as ACORN wage important campaigns fighting to regulate alternative providers. Non-bank institutions such as Calmeadow, Miziwe Biik, Access and the Black Creek Microfinance Program address business exclusion by making credit accessible to small business people; however, these services are limited in their outreach as they reach very small numbers (Foster, Berger, Ross, & Neglia, 2015; Hudson & Wehrell, 2005; Quarter, Ryan, & Chan, 2015; Spotton Visano, 2008). Whereas ROSCAs in Canada are meeting the needs of hundreds of people, they are seldom discussed as an alternative.Ordinary people dismayed by the greed and elitism of commercial bankers after the 2007-2008 financial crisis have turned to people-run banks (van Staveren, 2015). In 2015, during the financial crisis and Grexit vote, Greeks were coming up with financial self-help groups to cope when the banks crashed (North, 2015). In the U.K., British citizens have created a network called peer-to-peer lending, and they are pushing for legislation to recognize non-bank lending (Jones, 2014). People who find themselves in a state where they cannot access monies from a bank, usually low-income women, have always had to rely on their peers through ROSCAs to do the main part of their banking because of the business of exclusion in their society.ROSCAs are rotating savings and credit associations and they are also referred to as mutual aid groups, where the members make the rules and make regular contributions to a fund that is given in whole or in part to each member in turn.1 These collectives, practiced for centuries by people in the global south (Bouman, 1977), have become part of the financial landscape in large cities and towns. ROSCAs-locally known as susu, tontines, partner, meeting-turn, box-hand, sol, and many other names-are long-standing traditions of pooling resources that have historically helped excluded groups engage in alternative financial services.As people migrate they bring their version of ROSCA to their new countries, and these financial devices are embedded into a specific culture. Members use ROSCAs alongside the many devices they already use (Smets, 2000). The Ladies-a term coined by participants themselves while I carried out research in the Caribbean region (Hossein 2016; 2013)-organize the ROSCAs in a voluntary manner in an effort to meet their own economic needs and to develop community projects. The ROSCAs have also become a common practice among second-generation Canadians who also refer to themselves as Banker Ladies and who manage and participate in these institutions (Blackman & Brooks, 2002). …

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
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 enseignants0,090
Score d'incertitude au seuil0,650

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,007
Études des sciences et des technologies0,0230,005
Communication savante0,0060,002
Science ouverte0,0020,004
Intégrité de la recherche0,0010,003
Charge utile insuffisante (le modèle a refusé de juger)0,0060,001

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 Opus0,089
Tête enseignante GPT0,314
Écart entre enseignants0,226 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
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

Citations9
Publié2017
Routes d'admission2
Résumé présentoui

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Même revueCanadian journal of nonprofit and social economy researchMême sujetMicrofinance and Financial InclusionTravaux en français237 207