Equity and Community Art Education in the University: The Challenges, Possibilities, Implications of Learning in A Littoral Zone (A Critical Arts-informed Case Study)
Bibliographic record
Abstract
This critical, arts-informed case study examines how issues of equity emerge in the case of a community-arts certificate offered at a large urban Canadian university. A combination of arts-informed (poetry, micro-narratives, still/moving photography) and conventional qualitative methods of data collection, analysis, and representation is used with a focus on case study as storytelling for social justice. Community art has emerged as a relatively new credentialized field for teaching, practice, and research within the university/art school in Canadian contexts. Community arts courses in post-secondary settings often attempt to integrate collaborative grassroots and/or activist arts practices and initiatives for social justice into the context of the academy. In response, social justice arts practitioners outside the academic context have voiced concerns about access and credentialism within community-engaged art, and fine arts educators within the academy have raised questions about the artistic quality, rigor, and evaluation of practices that resist traditional disciplines, canons, and conceptions of art. This study explores how one particular community art certificate contributes to debates about legitimacy and equity in the fine arts and arts education: “What is art and who makes it? Where and why does art happen? How should art be cultivated?” The metaphor of a littoral zone is used throughout to examine the certificate as a liminal space that oscillates between different disciplinary paradigms, pedagogical approaches, and ways of knowing, being and doing. The research examines how issues of equity emerge in this case and how strategies that support equity are embraced (possibilities) or resisted (challenges) within the certificate and within the University’s cultures, practices and structures. A selection of the sites of learning (university, classroom, practica), relationships (interdisciplinary, institutional/organizational, interpersonal) and experiences (students) that the certificate embodies is examined. The research provides insight into how this particular story might address and intervene in the dominant conventions and relations of fine arts practice in Canada as well as contributing to discussions and movements for equity in Canadian post-secondary fine arts education and community-engaged arts practices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".