The transformative potential of community and collective arts pedagogies in Thunder Bay, Canada
Bibliographic record
Abstract
This dissertation presents the transformative potential of community art \ncollectives and outlines the pedagogical practices and decisions that contribute to their \nimpact in the community. The research took place in Thunder Bay, a small urban \ncommunity of roughly 110 000 people in Northwestern Ontario. Building on existing \nliterature and research on critical civic praxis I explored the relevance of this concept in \ncollective community arts settings. My research found artists engaged in praxis (the \ninterplay of critical reflection and practice), their actions informed by an understanding of \nsystemic oppression affecting their lives as they engaged in re-creating the world in order \nto transform it. \nThis is an arts-informed qualitative research study. Research data includes \ninterviews with 17 members of the artist community, enriched by my own experiences \nwith the arts and artist community in Thunder Bay. At the intersection of collective \nspace, public space, and art I developed an understanding of the relationship between arts \nand collective organizing in supporting critical civic praxis as everyday politics. The \ntransformation discussed by participants is connected to their worldviews and their social, \npolitical, and geographic location. In order to understand this transformative work I have \ndescribed the space these artists inhabit, the forms of oppression they encounter, and the \npractices that transformed their community. The pedagogical roots that feed participants? \nwork are authenticity, trust, humility, relationship (love), and critical reflection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.030 | 0.013 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".