Bibliographic record
Abstract
The suggestion that the Municipality of South Dundas should look at developing and implementing a Main Street Morrisburg Streetscape Project was highlighted in a recently completed report. The report was conducted under the Ontario Ministry of Agriculture, Food and Rural Affairs’ First Impressions Community Exchange (FICE) program. The FICE report in question was provided to the Municipality of South Dundas by representatives from the Town of Gananoque in September 2016 and this project was one of the major recommended action items that was contained within it (Zandbergen, 2016).For more than half a century, the Village of Morrisburg has lacked a proper Main Street Business District. It all started back in the mid-1950’s when about a third of the Village of Morrisburg, including the Main Street area, which was the original business district was lost forever under a wall of water. This was caused by the flooding required to construct the St. Lawrence Seaway due to the need to deepen the seaway to allow larger ships to navigate the river. In the process, Lake St. Lawrence was created. Because the flooding included significant parts of Morrisburg (including the central business district) along with other entire villages like Farran’s Point and Aultsville in Eastern Ontario, Morrisburg is included in some publications as what has become known as the Lost Villages.Keywords: Streetscape, First Impressions Program, Main Street, Business District, Lost Villages
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.034 | 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".