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Record W4300817676 · doi:10.1093/cdj/bsac025

‘Participation—with what money and whose time?’ An intersectional feminist analysis of community participation

2022· article· en· W4300817676 on OpenAlexaboutno aff
Julia Fursova, Denise Bishop-Earle, Kisa Hamilton, Gillian Kranias

Bibliographic record

VenueCommunity Development Journal · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsTechnocracyCommunity engagementPublic relationsCommunity developmentSociologySnowball samplingCommunity organizationCitizen journalismPoliticsPublic administrationPolitical scienceEconomic growthEconomics

Abstract

fetched live from OpenAlex

Abstract The paper presents the results of community-based participatory action research that evaluated the quality and extent of resident participation in community development projects initiated by a network of non-profit and public agencies in a lower-income, racialized neighbourhood in Toronto. The paper examines dynamics of community engagement and volunteer participation in relation to the socio-political context of neoliberal urban development within which they unfold. Against this backdrop, the paper discusses processes of normalization and the mainstreaming of a technocratic or instrumental approach to community engagement. The paper argues how this instrumental approach extracts volunteer participation from residents to meet short-term organizational targets while offering no genuine opportunity for residents to co-create long-term, meaningful solutions to community needs and priorities. Such short-term, ‘band-aid’ community engagement and capacity building projects contribute to a crisis of trust between residents and the non-profit agencies. The paper presents a community engagement continuum mapping indicators for technocratic and extractivist community engagement in contrast to indicators for transformative and empowering processes.

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)0.005
metaresearch head score (Gemma)0.004
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0100.030
Scholarly communication0.0070.004
Open science0.0010.005
Research integrity0.0010.001
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 head0.120
GPT teacher head0.436
Teacher spread0.316 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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