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Record W2998239130 · doi:10.1002/ajcp.12411

Building Communities in Tense Times: Fostering Connectedness Between Cultures and Generations through Community Arts

2019· article· en· W2998239130 on OpenAlexafffundabout
Caroline Beauregard, Joëlle Tremblay, Janie Pomerleau, Maïté Simard, Élise Bourgeois-Guérin, Claire Lyke, Cécile Rousseau

Bibliographic record

VenueAmerican Journal of Community Psychology · 2019
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsMcGill UniversityUniversité TÉLUQUniversité LavalUniversité du Québec en Abitibi-TémiscamingueUniversité du Québec à Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsThe artsSocial connectednessSociologyPsychological resilienceHealth psychologySpace (punctuation)Social psychologyPsychologyPublic relationsPublic healthVisual artsPolitical scienceMedicineArtNursing

Abstract

fetched live from OpenAlex

The worldwide upsurge in social polarizations generates intercommunity tensions that challenge the social fabric of urban neighborhoods and undermine the relationships between their members. Because community arts can foster the creation of connections between people that would not have been in contact otherwise, they are often perceived as being powerful tools to foster community resilience. Through a multiple case study approach, this article describes how three community arts projects, carried out in two socioeconomically deprived neighborhoods of Montreal (Canada), influenced the social relationships between participants from diverse ethnocultural backgrounds and generations. Using participant observation and arts-based data collection methods (photography, video, and arts productions), the authors examine how the three projects illustrate (a) the interactive processes at play, (b) the transmission and hybridization of stories and images of adversity and resiliency, and (c) the access to a collective voice.

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)0.004
metaresearch head score (Gemma)0.006
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 score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0190.018
Scholarly communication0.0080.004
Open science0.0020.017
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.200
GPT teacher head0.512
Teacher spread0.313 · 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

Citations36
Published2019
Admission routes3
Has abstractyes

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