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Enregistrement W2982042461 · doi:10.1353/gpr.2019.0034

Small Cities, Big Issues: Reconceiving Community in a Neoliberal Era ed. by Christopher Walmsley and Terrance Kading

2019· article· en· W2982042461 sur OpenAlexaboutno aff
Mervyn Horgan

Notice bibliographique

RevueGreat Plains research · 2019
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueRural development and sustainability
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSociologyScale (ratio)Political scienceEconomic historyGeographyHistoryCartography

Résumé

récupéré en direct d'OpenAlex

Reviewed by: Small Cities, Big Issues: Reconceiving Community in a Neoliberal Era ed. by Christopher Walmsley and Terrance Kading Mervyn Horgan Small Cities, Big Issues: Reconceiving Community in a Neoliberal Era. Edited by Christopher Walmsley and Terrance Kading. Edmonton: AU Press, 2018. ix + 334 pp. Figures. $37.95 paper. The social scientific study of small cities is woefully underdeveloped. It's a curious foible of social research that work on small cities tends to be more the domain of rural researchers who scale up from small rural communities to small cities, and less the domain of urban researchers who tend instead to train their vision on big issues facing big cities, leaving aside entirely the social dynamics of small cities. Consequently, studies of both small rural communities and of big cities abound, but little work focuses on the specificity of small cities. This tendency is most certainly a loss for urban researchers (and a mea culpa is in order here), as many of the processes at play in large metropolises are equally, if not more, tangible and visible in smaller cities. Moreover, as the contributors to this highly readable and thoughtfully edited volume show, all too often small cities are collateral damage when broad-scale structural transformations—rent primarily by neoliberal economic policies—are underway. As the editors note in their introduction, "small is . . . a relative term," thus making a universally applicable definition near impossible. As the majority of the chapters in the collection are based on case studies from small Canadian cities, the editors pragmatically adopt a somewhat fluid definition treating small cities as those with a population between 10,000 and 100,000, with some wiggle room at each end. Given the relative underdevelopment of what we might call the "small cities subfield," kudos are due to the editors of this fascinating collection for bringing together scholars and practitioners researching and working across a wide range of fields including sociology, social work, political science, and mental health. Each chapter shows that one barely needs to scratch the surface in small cities to very quickly reveal big issues at play. Across 12 well-written and thematically coherent chapters, I learned about homelessness, illicit drug use, sex work, queerness, deinstitutionalization, incarceration and parole, aboriginal peoples, planning and governance, immigrant settlement, poverty reduction, and community empowerment. Chapter by chapter it became clearer that small cities are sites of "serious inequities and social tensions," which as most authors demonstrate, quite clearly derive from state disinvestment and increasingly punitive social policy. One minor gripe with this book: the absence of an index makes quick access to specific topics more difficult, though to be fair, in addition to the reasonably priced paper copy of the book, AU Press is to be commended for adopting a hybrid publishing model that also makes this book freely available as an open access digital download, so terms can be searched on the portable document format (PDF). Overall, Small Cities, Big Issues advances a critical and timely analysis of the state of small Canadian cities in the neoliberal era. In contemporary social science, I sometimes feel like "neoliberalism" is a catchall buzzword or an inconsistently applied analytic term, but as the research on small cities reported in this book very clearly demonstrates, neoliberalism's everyday effects are consistently devastating to communities. [End Page 169] Mervyn Horgan Department of Sociology and Anthropology University of Guelph, Canada Copyright © 2019 Center for Great Plains Studies, University of Nebraska–Lincoln

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)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,144
Score d'incertitude au seuil0,991

Scores Codex et Gemma par catégorie

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

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 Opus0,073
Tête enseignante GPT0,291
Écart entre enseignants0,217 · 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.

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

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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