Darning the community fabric: an architectural language of healing and repair
Bibliographic record
Abstract
This thesis investigates a language of development in rural Ontario communities \nusing a process of architectural darning. Through the analysis of metaphor as a human \nprocess, landscape is understood through a method of weaving and understanding the \nembodiment of place through process. Colonial understandings of land and cadastral \nmapping practices reduce place to a unit of economic power, severing the connection \nbetween it and the person. This thesis argues that place is the process of living \nmemory and the creation of agency through shared experience. Applying the darning \nprocess to the region Grey County, Ontario, tears in the fabric can be observed as a \nconsequence of colonial extraction and a landscape of violence applied to Indigenous \npeoples. Manifesting place in learning begins the journey to reconciliation, utilizing \nthe approaches in two-eyed seeing and the agency in continuous local learning. The \njourney of the healing process takes place within the people who engage in site and \nadd to the body of knowledge.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.040 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".