A Storied History of Art Education: The Art Department at Central Technical School, 1892-2014
Bibliographic record
Abstract
A Storied History of Art Education: The Art Department at Central Technical School, 1892-2014 \nDustin Garnet, Ph.D. \nConcordia University, 2015 \n \nThe Art Department at Central Technical School (CTS) in Toronto, Canada supports the \ncountries first and only specialized technical fine art program for adults and high school students. \nMy purpose in this research is to provide one version of this institution’s 122 year history \nutilizing the lived experiences of the men and women who shared in its legacy. I explore how \nstories as a form of historical research provide insights into the everyday lives and artistic culture \nof CTS resulting in more localized and relational accounts of the past. Questions guiding this \nstudy include: Who were the forces behind the growth of the CTS art program? What are the \nfactors that have helped sustain this publically funded institution? What were the major historical \nevents that shaped the history of CTS? And, why is the Art Department at CTS rarely mentioned \nin written histories of Canadian art education? \nFrom a theoretical perspective, my approach to new history(ies) has generated a socio-historical literary account of CTS as part of the field of art education, allowing me to construct \nstories and emplot characters in ways that provide multiple forms and contexts to understand the \ninstitution from more holistic perspectives. Through the methodological architecture of the \npolyptych frame I have built a collection of historical stories that hinge together, but can be \nseparated and reconfigured to tell multiple stories from personal, external, and internal \nperspectives. Stories are at the heart of my research and within them lies much more than \nindividual oral histories. The new history I construct speaks to a transgenerational artistic culture \niv \nbuilt on relationships and networks that directly contribute to shaping the visual culture of \nCanada. \nInvoking the use of stories as an aesthetic means of constructing history has permitted me \nto expand on significant historical issues specifically addressing the domains of art, education, \nsocial structure, and culture. In an effort to promote genealogical continuity rather than disparity \nbetween historical realities and historical narratives I engaged in primary sources of information \nthat link five generations and identify four thematic threads including, identity politics, \ninstitutional identity, school culture, social networks, that braid and create continuity over time.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".