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Record W2135943738 · doi:10.1093/cdj/bst001

When words arrive: a qualitative study of poetry as a community development tool

2013· article· en· W2135943738 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCommunity Development Journal · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCommunity and Sustainable Development
Canadian institutionsMcGill UniversityCommunity Based Research Centre
FundersMcGill University
KeywordsPoetryThe artsCommunity developmentContext (archaeology)SociologyCreative writingQualitative researchAction (physics)CreativityVisual artsPsychologySocial scienceSocial psychologyArtLiteraturePolitical scienceHistoryLaw

Abstract

fetched live from OpenAlex

Poetry, among the arts, remains understudied as a means for community development. To address this scarcity, this paper considers the use of poetry as a community development tool and discusses its uniqueness in this role. It offers a description and analysis of an exploratory, qualitative research study carried out with twelve respondents in Montreal, Canada, who participated in community-based creative writing groups. Evaluation suggested that, overall, the poetry groups made a positive contribution to community building and development. This paper locates the study in the context of community development and the arts and includes references to poetry therapy and social action-based creative writing. It also raises questions as to why poetry has not found its place on the agenda of arts-based community development.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0140.001
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0020.000

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 head0.070
GPT teacher head0.375
Teacher spread0.305 · 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