Visual culture jam : art, pedagogy and creative resistance
Bibliographic record
Abstract
I seek to understand the role that art education might play in the development of socially engaged students. Informed by theorists in critical, social reconstructive and visual culture art education, I explore how engagement with social issues through the examination and production of visual culture impacts students' understanding and awareness about these social issues. I also examine how this engagement influences students' understanding and awareness of the social roles and cultural functions of art/visual culture. Located within a Visual Arts 11/12 classroom in an inner city Canadian high school, this study addresses omissions in the educational literature; specifically the paucity of data supporting the conceptual connections being made among the art/visual culture, education, and social issues. While art and art education are regularly promoted by educational theorists as catalysts for social and individual change, few studies have concentrated on high school students working in classroom settings. Working as an artist/researcher/teacher over the course of three months, I adopt a relational approach to the study, which is informed by a/r/t/ography, hermeneutics, visual ethnography, and action research. This pluralistic methodology includes a rejection of hierarchical conceptualizations that portray research as something that is done to students, rather than with them. As such, the students are actively involved in the collection of visual data, including digital video and photographs. Data collection also includes ethnographic interviews, student written responses, field notes, and critical research reflections. Art making is used throughout as an important component of the meaning-making process. Conceptualized and created as an academic assemblage, this dissertation is a contiguous fusion of research images and texts. It conlcudes by outlining how engagement in social issues through art/visual culture can increase students' understanding and awareness of those issues. It also shows how this engagement can provide an increased comprehension of the connections between art/visual culture and the sociocultural sphere. The dissertation ends by illustrating how engagement through the production of art/visual culture can empower students with a sense of social agency, voice and hope.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.012 | 0.038 |
| Scholarly communication | 0.027 | 0.008 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".