Bibliographic record
Abstract
Rooted in the disciplinary traditions of Fine Arts, Geography, and Cultural Studies, this thesis seeks to understand how an understanding of melancholy and longing related to memories of one's familiar cultural landscape illuminates a place-based Francophone cultural identity. \nTo understand the unique elements of northern Francophone Ontarian cultural landscapes and define northern familiarities, I pose the following questions. 1) What images of Sudbury's landscape are reflective of Francophone cultural identity? 2) Does juxtaposing Sudbury's cultural landscape images with images of an estranged location highlight the unique elements of Sudbury's cultural landscape? 3) Can place-based cultural identity be defined by visualizing the affects of longing, melancholy and stranger-ness when creating art-based research of Francophone Ontarian northerners from Sudbury. The creation of 3 large paintings accompanied by 100 postcards were exhibited in Sudbury and in Toronto in search of the answers to these questions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.060 | 0.003 |
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".