Heritage conservation planning in Saint John, New Brunswick: The importance of heritage conservation and looking to a future with social justice
Bibliographic record
Abstract
Canada has a long history of Heritage conservation across all levels of government and through the use of many different tools. Canada is also a multicultural diverse nation, but often it has focused on one dominant narrative in heritage, often centered on the affluent and rich or colonial powers. Heritage is not just built aesthetic style, but the intangible evolution of our relationships with space. Heritage is part of our identity and fosters a sense of community; without the full story we are lesser. We need to ask ourselves, who and how is heritage designated in our system, whose heritage has this conserved, and as we move forward, how can we bring a social justice lens to our planning. Using a case study of Saint John, New Brunswick, the oldest incorporated city in Canada with a large amount of conserved heritage, we can start to see who has been involved in designating and conserving heritage. Interviews with people involved will also help to bring into focus perceptions of who decides what is heritage worthy and how they think we could improve heritage planning. We are trying to improve our planning system so that in the future, our heritage conservation better reflects our diversity as Canadians.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.038 | 0.011 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".