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Record W1608907365

Education and Social Innovation: The Youth Uncensored Project—A Case Study of Youth Participatory Research and Cultural Democracy in Action

2015· article· en· W1608907365 on OpenAlexaffvenueabout
Diane Conrad

Bibliographic record

VenueCanadian Journal of Education / Revue canadienne de l éducation · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMetisParticipatory action researchSociologyIndigenousAction researchScholarshipThe artsPublic relationsEngaged scholarshipPhotovoiceDemocracyGovernment (linguistics)Traditional knowledgeSocial sciencePedagogyPolitical sciencePoliticsEconomic growth
DOInot available

Abstract

fetched live from OpenAlex

This article discusses social innovation in education informed by arts-based and Indigenous ways of knowing. I use the term Indigenous to refer to First Peoples’ and their wisdom traditions from places around the world and the term Aboriginal to refer to the diverse First Nations, Metis, and Inuit peoples of Canada. The article looks at the ethical imperative for doing socially innovative work, and examines practices with potential for embedding social innovation in educational scholarship, including experiential and relational educational approaches, such as community-service learning and restorative justice; participatory action research as an allied research approach; and community arts framed as cultural democracy. It describes a research project with street-involved youth as a case study for research that moves toward social innovation through the Government of Canada Policy Research Initiative’s five steps involved in a co-creative social innovation project.

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)0.019
metaresearch head score (Gemma)0.011
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 score0.091
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0300.022
Scholarly communication0.0090.004
Open science0.0030.013
Research integrity0.0030.005
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 head0.859
GPT teacher head0.633
Teacher spread0.226 · 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

Citations42
Published2015
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Education / Revue canadienne de l éducationSame topicParticipatory Visual Research MethodsFrench-language works237,207