Mapping historical Mississauga: Uncovering the city's changing landscapes online using historical maps and digital data
Bibliographic record
Abstract
The City of Mississauga is very young by Canadian standards, becoming a town in 1968 and reaching city status in 1974. In this short time, Mississauga has evolved from a loose rural grouping of villages and hamlets with a combined population of about 95,000 to being the sixth largest city in Canada with a population today of over 720,000. For better or worse, Mississauga is often held up as a case study of post-World War II urban change, and as an emergent Canadian suburb. One of the best resources for exploring this change is through the use of maps and digital data. The Scholars GeoPortal, a geospatial data discovery and delivery service, provides access to hundreds of maps and geospatial datasets related both to modern day and historical Mississauga, some of which also provide coverage on a national scale. Our presentation will highlight many of these resources and outline how they can provide research impact in various disciplines. By allowing researchers to track the development of Mississauga using maps and data that span the most important decades of the city's history, the Scholars GeoPortal provides a means to discover, analyse, visualize, and teach historical Mississauga.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".