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Record W2496390766 · doi:10.1093/cdj/bsw027

The ‘business of community development’ and the right to the city: reflections on the neoliberalization processes in urban community development

2016· article· en· W2496390766 on OpenAlexaboutno aff
Julia Fursova

Bibliographic record

VenueCommunity Development Journal · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsNeoliberalism (international relations)CommonsRestructuringHegemonyCommunity developmentSociologyCommunity economic developmentCommunity organizationAutonomyEconomic growthPolitical sciencePolitical economyPublic administrationPoliticsEconomicsLaw

Abstract

fetched live from OpenAlex

Abstract The paper explores emerging contradictions in community development, a subset of non-profit sector, within the context of neoliberalization. I examine non-profit sector as a site that has a potential for articulating counter-hegemonic discourse alternative to neoliberalism. Conversely, non-profit sector itself has been subjected to neoliberal co-optation and restructuring that resulted in restricted autonomy of the sector and decreased capacity to advocate for progressive social change. Drawing on my experience as a community engagement worker in one of Toronto's neighbourhood improvement areas, I problematize community development, posing questions about the role of the non-profit agencies in the production of specific socio-economic configurations that may, albeit inadvertently, support neoliberal discourse. Through an example of local community campaign for increased access to public space and services, I highlight options to enhance counter-hegemonic potential of community development as a critical practice aimed at advancing the commons.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.100
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0280.168
Scholarly communication0.0160.007
Open science0.0020.014
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.135
GPT teacher head0.404
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations39
Published2016
Admission routes1
Has abstractyes

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